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Join discussions  in order to build understanding of concepts in service science.  Here is our curriculum guide.

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 Service Science and Service Researchers

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Some papers on service innovation

Service Innovation Pointers

 

This is an good place to get started:

Service Innovation Triangle – https://www.youtube.com/watch?v=02_5TOEugvE

 

0. Tidd & Hull (UK)

Tidd, J., & Hull, F. M. (2003). Service Innovation: Organizational responses to technological opportunities & market imperatives (Vol. 9). Imperial College Press.

1. Ian Miles (UK)

Miles, I. (2005). Innovation in services. The Oxford handbook of innovation, 16, 433-458.

Metcalfe, J. S., & Miles, I. (2000). Innovation systems in the service economy. Measurement and Case Study Analysis, 2.

Miles, I. (2008). Patterns of innovation in service industries. IBM Systems journal, 47(1), 115-128.

2. Henry Chesbrough (USA)

Chesbrough, H. (2010). Open services innovation: rethinking your business to grow and compete in a new era. John Wiley & Sons.

Chesbrough, H., & Spohrer, J. (2006). A research manifesto for services science. Communications of the ACM, 49(7), 35-40.
3. Bo Edvardsson (Nordic)

Edvardsson, B., Gustafsson, A., Sandén, B., & Johnson, M. D. (2000). New service development and innovation in the new economy.
4. Mary Jo Bitner (USA)

Bitner, M. J., Ostrom, A. L., & Morgan, F. N. (2008). Service blueprinting: a practical technique for service innovation. California management review, 50(3), 66.

Cadwallader, S., Jarvis, C. B., Bitner, M. J., & Ostrom, A. L. (2010). Frontline employee motivation to participate in service innovation implementation. Journal of the Academy of Marketing Science, 38(2), 219-239.
5. Len Berry (USA)

Berry, L. L., Shankar, V., Parish, J. T., Cadwallader, S., & Dotzel, T. (2006). Creating new markets through service innovation.
6. Jay Kandampully (USA)

Kandampully, J. (2002). Innovation as the core competency of a service organisation: the role of technology, knowledge and networks. European Journal of Innovation Management, 5(1), 18-26.

7. Van Riel (Netherlands)

Van Riel, A. C., Lemmink, J., & Ouwersloot, H. (2004). High‐Technology Service Innovation Success: A Decision‐Making Perspective. Journal of Product Innovation Management, 21(5), 348-359.

8. Rohit Verma (USA) – hospitality industry

Victorino, L., Verma, R., Plaschka, G., & Dev, C. (2005). Service innovation and customer choices in the hospitality industry. Managing Service Quality, 15(6), 555-576.
9. Den Hertog (Netherlands)

Den Hertog, P., Van der Aa, W., & de Jong, M. W. (2010). Capabilities for managing service innovation: towards a conceptual framework. Journal of Service Management, 21(4), 490-514.

10. Renu Argawal (Australia)

Agarwal, R., & Selen, W. (2009). Dynamic capability building in service value networks for achieving service innovation. Decision sciences, 40(3), 431-475.
11. Van Ark (Netherlands)

Van Ark, B., Broersma, L., & den Hertog, P. (2003). Services innovation, performance and policy: a review. Synthesis Report in the Framework of the Project on Structural Information Provision on Innovation in Services (SIID) for the Ministry of Economic Affairs of the Netherlands. Groningen: University of Groningen and DIALOGIC.

12. Ordanini (Italy)

Ordanini, A., & Parasuraman, A. (2010). Service innovation viewed through a service-dominant logic lens: a conceptual framework and empirical analysis. Journal of Service Research, 1094670510385332.

13. Lievens (Netherlands, Belgium?) – financial services

Lievens, A., & Moenaert, R. K. (2000). Project team communication in financial service innovation. Journal of Management Studies, 37(5), 733-766.

14. Alam (?UK)

Alam, I. (2006). Service innovation strategy and process: a cross-national comparative analysis. International Marketing Review, 23(3), 234-254.

15. Chan (Hong Kong)

Chan, A., Go, F. M., & Pine, R. (1998). Service innovation in Hong Kong: attitudes and practice. Service Industries Journal, 18(2), 112-124.

16. Martin (Germany)

Martin, C. R., Horne, D. A., & Schultz, A. M. (1999). The business-to-business customer in the service innovation process. European Journal of Innovation Management, 2(2), 55-62.

17. Bettencourt (USA)

Bettencourt, L. (2010). Service innovation: How to go from customer needs to breakthrough services. London: McGraw-Hill.

18. Song (Korea?)

Song, L. Z., Song, M., & Di Benedetto, C. A. (2009). A Staged Service Innovation Model*. Decision Sciences, 40(3), 571-599.

19. Tor Andreassen (Norway)

Andreassen, T. W., & Streukens, S. (2009). Service innovation and electronic word-of-mouth: is it worth listening to?. Managing Service Quality, 19(3), 249-265.
20. Kim (Korea)
21. Paswan (?)

Paswan, A., D’Souza, D., & Zolfagharian, M. A. (2009). Toward a contextually anchored service innovation typology. Decision Sciences, 40(3), 513-540.
22. Spohrer & Maglio (IBM USA) – Z model of service evolution

Spohrer, J., & Maglio, P. P. (2008). The emergence of service science: Toward systematic service innovations to accelerate co‐creation of value. Production and operations management, 17(3), 238-246.

23. Bessant (?)

Bessant, J., & Davies, A. (2007). 3 Managing service innovation. Innovation in services, 61.
24. Arai (Japan)

Hara, T., Arai, T., & Shimomura, Y. (2009). A CAD system for service innovation: integrated representation of function, service activity, and product behaviour. Journal of Engineering Design, 20(4), 367-388.

25. Jones (IDEO USA)

Jones, M., & Samalionis, F. (2008). From small ideas to radical service innovation. Design Management Review, 19(1), 20-26.

26. Fynes (Ireland)

Fynes, B., & Lally, A. M. (2008). Innovation in services: From service concepts to service experiences. In Service science, management and engineering education for the 21st century (pp. 329-333). Springer US.

27. Kowalkowski (Nordics)

Kindström, D., Kowalkowski, C., & Sandberg, E. (2013). Enabling service innovation: a dynamic capabilities approach. Journal of Business Research, 66(8), 1063-1073.

Carlborg, P., Kindström, D., & Kowalkowski, C. (2014). The evolution of service innovation research: a critical review and synthesis. The Service Industries Journal, 34(5), 373-398.
28. Robert Paton (UK)

Paton, R. A., & McLaughlin, S. (2008). Services innovation:: Knowledge transfer and the supply chain. European Management Journal, 26(2), 77-83.

29. IBM
30. IBM and Cambridge UK
31. PWC

32. EU

33. Sundbo

34. Dorothy Riddle (USA – ServiceGrowth.org)

34. Scott Sampson (USA)

35.  Service Design & Innovation (long)

36.  Service Innovation & Design (short)

37.  UN

38. Service Innovation Triangle – https://www.youtube.com/watch?v=02_5TOEugvE

ISSIP Meetup: Concept Mapping

Four of us met recently do work on concept mapping at SJSU Business School Santa Clara campus. Prof. Steve Kwan (SJSU), Yassi Moghaddam (ISSIP), Jim Spohrer (IBM), and Fan Xiucheng (Fudan).

We reviewed the BORO Method.

BORO Method

We studied S-D Logic Foundational Propositions.

SD LOgic Foundations

We studied Service Science Foundational Concepts:

Service Science 12 Concepts

Extract 28 phrases/candidate concepts from S-D Logic propositions:

  1. 11 ways to refer to entities (most with rights and responsibility, owned by, or composed of)
    1. Resource integrator
    2. Customer
    3. Beneficiary
    4. Actor
    5. Social and economic actor
    6. Enterprise
    7. Operant Resources (people)
    8. Economies
    9. Service economies
    10. Co-creator of value
    11. Goods
  2. 17 other concepts
    1. Value
    2. Value in exchange
    3. Value in use
    4. Value in context
    5. Fundamental basis of exchange
    6. Indirect exchange
    7. Exchange
    8. Economic Exchange
    9. Market Exchange
    10. Social Exchange
    11. Interaction
    12. Competitive advantage
    13. Distribution mechanism
    14. Uniquely and phenomenologically determined
    15. Inherently customer oriented and relational
    16. Service
    17. Service Oriented view (people have view; a service oriented is a view)
    18. Value proposition (people can communicate a value proposition, organization can communicate value proposition)

Extracted 16 phrases/candidate concepts from Service Science: Conceptual Framework

  1. Ecology
  2. Entity
  3. Interaction
  4. Outcome
  5. Value Propositions
  6. Governance Mechanisms
  7. Access Rights
  8. Resources
  9. Measures
  10. Stakeholders
  11. Identity
  12. Reputation
  13. Capabilities
  14. Constraints
  15. Rights
  16. Responsibilities

We then created the following 41 knowledge triples (relationship concept1 concept2) as part of a concept map:

[isa service_system_entity entity]
[isa resource_integrator entity]
[isa customer entity]
[isa beneficiary entity]
[isa actor entity]
[isa social_and_economic_actor entity]
[isa enterprise entity][isa operant_resource entity]
[isa co-creator_of_value entity]
[isa economy entity]
[isa service_economy entity]
[isa goods resource]
[isa operand_resource resource]
[isa operant_resource resource]
[isa entity resource]

[isa value expected_outcome]
[isa value perceived_outcome]
[isa value realized_outcome]
[typeof expected_outcome outcome]
[typeof perceived_outcome outcome]
[typeof realized_outcome outcome]
[typeof value_in_exchange value]
[typeof value_in_use value]
[typeof value_in_context value]
[isa fundamental_basis_of_exchange interaction]
[isa indirect_exchange interaction]
[isa direct_exchange interaction]
[isa economic_exchange interaction]
[isa social_exchange interaction]
[isa market ecology]
[propertyof entity competitive_advantage]
[propertyof offering distribution_mechanism]
[isa offering value_proposition]
[propertyof interaction uniquely_and_phenomenologically_determined]
[propertyof entity view]
[typeof service-oriented_view view]
[propertyof service inherently_customer-oriented_and_relational]
[typeof value_proposition interaction]
[typeof governance_mechanism interaction]
[typeof service interaction]
[typeof service outcome]
[typeof service entity]

Before doing the above we spent time building a concept map for the type of service system known as a college, university, institute of higher education.   The idea was do case-based-reasoning before looking at knowledge triples (relationship concept1 concept2) for a concept map.  We generated a very large number of knowledge triples including:

[hasrole faculty university]
[hasrole student university]
[hasrole parent university]
[hasrole deans university]
[hasrole staff university]
[hasrole administration university]
[hasrole teaching_assistant university]
[hasrole adjunct_faculty university][hasrole alumni university]
[hasrole prospects university]
[hasplace campus university]
[hasplace facilities university]
[hasplace classroom university]
[hasplace laboratory university]
[hasplace faculty_office university]
[hasplace administrator_office university]
[hasplace library university]
[hasplace sports_stadium university]
[hasplace dormitory university]
[hasplace dorm_room university]
[hasplace cafeteria unversity]
[teaches faculty students]
[managers deans faculty]
[teachin faculty classroom]
[learnsfrom students faculty]
[haspart campus facility]
[haspart building classroom]
[haspart classroom desks]
[haspart classroom seats]
[haspart classroom podium]
[haspart dormitory dorm_room]
[admits admissions prospect]
[rejects admissions prospect]
[waitlists admissions prospect]

I also wrote a Python program to extract information form MIT Concept Net 5.

[‘Antonym’, ‘university’, ‘primary_school’]
[‘AtLocation’, ‘atheist’, ‘university’]
[‘AtLocation’, ‘book’, ‘university’]
[‘AtLocation’, ‘classroom_chair’, ‘university’]
[‘AtLocation’, ‘computer’, ‘university’]
[‘AtLocation’, ‘druge’, ‘university’]
[‘AtLocation’, ‘hard_work_faculty’, ‘university’]
[‘AtLocation’, ‘landscape’, ‘university’]
[‘AtLocation’, ‘openmind’, ‘university’]
[‘AtLocation’, ‘plane’, ‘university’]
[‘AtLocation’, ‘professor’, ‘university’]
[‘AtLocation’, ‘projectile’, ‘university’]
[‘AtLocation’, ‘see_professor’, ‘university’]
[‘AtLocation’, ‘student’, ‘university’]
[‘AtLocation’, ‘teach_assistant’, ‘university’]
[‘AtLocation’, ‘thinker’, ‘university’]
[‘AtLocation’, ‘university’, ‘chemistry_lab’]
[‘AtLocation’, ‘venus’, ‘university’]
[‘CapableOf’, ‘university’, ‘honor_good_student’]
[‘EtymologicallyDerivedFrom’, ‘antiuniversity’, ‘university’]
[‘EtymologicallyDerivedFrom’, ‘multiversity’, ‘university’]
[‘EtymologicallyDerivedFrom’, ‘universitylike’, ‘university’]
[‘HasA’, ‘university’, ‘classroom’]
[‘IsA’, ‘university’, ‘academy’]
[‘IsA’, ‘university’, ‘college’]
[‘IsA’, ‘university’, ‘musical_instrument’]
[‘IsA’, ‘university’, ‘place’]
[‘IsA’, ‘university’, ‘place_for_learn’]
[‘IsA’, ‘university’, ‘school’]
[‘LocationOfAction’, ‘argue’, ‘university’]
[‘PartOf’, ‘department’, ‘university’]
[‘RelatedTo’, ‘academian/n’, ‘university’]
[‘RelatedTo’, ‘antiuniversity/a’, ‘university’]
[‘RelatedTo’, ‘asu’, ‘university’]
[‘RelatedTo’, ‘cantabrigian/a’, ‘university’]
[‘RelatedTo’, ‘college’, ‘university’]
[‘RelatedTo’, ‘dean/n’, ‘university’]
[‘RelatedTo’, ‘department’, ‘university’]
[‘RelatedTo’, ‘fac_brat/n’, ‘university’]
[‘RelatedTo’, ‘faculty/n’, ‘university’]
[‘RelatedTo’, ‘graduate/n’, ‘university’]
[‘RelatedTo’, ‘greek_house/n’, ‘university’]
[‘RelatedTo’, ‘hilary_term/n’, ‘university’]
[‘RelatedTo’, ‘laureate/n’, ‘university’]
[‘RelatedTo’, ‘legacy_student/n’, ‘university’]
[‘RelatedTo’, ‘major/v’, ‘university’]
[‘RelatedTo’, ‘nonuniversity/a’, ‘university’]
[‘RelatedTo’, ‘princeton/n’, ‘university’]
[‘RelatedTo’, ‘proproctor/n’, ‘university’]
[‘RelatedTo’, ‘rag_day/n’, ‘university’]
[‘RelatedTo’, ‘rag_week/n’, ‘university’]
[‘RelatedTo’, ‘repetitor/n’, ‘university’]
[‘RelatedTo’, ‘schoolman/n’, ‘university’]
[‘RelatedTo’, ‘sessional/n’, ‘university’]
[‘RelatedTo’, ‘student/n’, ‘university’]
[‘RelatedTo’, ‘tutor/n’, ‘university’]
[‘RelatedTo’, ‘undergraduate/n’, ‘university’]
[‘RelatedTo’, ‘university’, ‘degree’]
[‘RelatedTo’, ‘university’, ‘get’]
[‘RelatedTo’, ‘university’, ‘graduate’]
[‘RelatedTo’, ‘university’, ‘learn_place’]
[‘RelatedTo’, ‘university’, ‘school’]
[‘RelatedTo’, ‘uva’, ‘university’]
[‘UsedFor’, ‘student’, ‘university’]
[‘UsedFor’, ‘university’, ‘cooperation’]
[‘UsedFor’, ‘university’, ‘degree’]
[‘UsedFor’, ‘university’, ‘eat_food_with’]
[‘UsedFor’, ‘university’, ‘teach’]
Files: 2 Total Assertions: 1660281 English_assertions 1066922
[‘AtLocation’, ‘argue’, ‘university’]
[‘AtLocation’, ‘auditorium’, ‘university’]
[‘AtLocation’, ‘beautiful_mind’, ‘university’]
[‘AtLocation’, ‘college_student’, ‘university’]
[‘AtLocation’, ‘football_team’, ‘university’]
[‘AtLocation’, ‘hotdog’, ‘university’]
[‘AtLocation’, ‘human’, ‘university’]
[‘AtLocation’, ‘knoledge’, ‘university’]
[‘AtLocation’, ‘knowledge’, ‘university’]
[‘AtLocation’, ‘lot_of_girl’, ‘university’]
[‘AtLocation’, ‘mathematics’, ‘university’]
[‘AtLocation’, ‘newspaper’, ‘university’]
[‘AtLocation’, ‘pen’, ‘university’]
[‘AtLocation’, ‘poet’, ‘university’]
[‘AtLocation’, ‘rational_thinker’, ‘university’]
[‘AtLocation’, ‘research’, ‘university’]
[‘AtLocation’, ‘scissor’, ‘university’]
[‘AtLocation’, ‘squirrell_in_tree’, ‘university’]
[‘AtLocation’, ‘stapler’, ‘university’]
[‘AtLocation’, ‘sunset’, ‘university’]
[‘AtLocation’, ‘teacher’, ‘university’]
[‘AtLocation’, ‘university’, ‘drawer’]
[‘AtLocation’, ‘university’, ‘professor’]
[‘InstanceOf’, ‘ufscar’, ‘university’]
[‘IsA’, ‘university’, ‘bookstore’]
[‘IsA’, ‘university’, ‘research_organization’]
[‘RelatedTo’, ‘academical/a’, ‘university’]
[‘RelatedTo’, ‘alumnus_association/n’, ‘university’]
[‘RelatedTo’, ‘arbor’, ‘university’]
[‘RelatedTo’, ‘biocentre/n’, ‘university’]
[‘RelatedTo’, ‘chu’, ‘university’]
[‘RelatedTo’, ‘dead_week/n’, ‘university’]
[‘RelatedTo’, ‘doctorate/n’, ‘university’]
[‘RelatedTo’, ‘extramural/a’, ‘university’]
[‘RelatedTo’, ‘fellow’, ‘university’]
[‘RelatedTo’, ‘frat_boy/n’, ‘university’]
[‘RelatedTo’, ‘fraternity/n’, ‘university’]
[‘RelatedTo’, ‘gownsman/n’, ‘university’]
[‘RelatedTo’, ‘high_education/n’, ‘university’]
[‘RelatedTo’, ‘hogeschool/n’, ‘university’]
[‘RelatedTo’, ‘intervarsity/a’, ‘university’]
[‘RelatedTo’, ‘lecture’, ‘university’]
[‘RelatedTo’, ‘lecturer’, ‘university’]
[‘RelatedTo’, ‘letter_and_science/n’, ‘university’]
[‘RelatedTo’, ‘literature’, ‘university’]
[‘RelatedTo’, ‘little-go/n’, ‘university’]
[‘RelatedTo’, ‘multiversity/n’, ‘university’]
[‘RelatedTo’, ‘nostrificate/v’, ‘university’]
[‘RelatedTo’, ‘nostrification/n’, ‘university’]
[‘RelatedTo’, ‘party_school/n’, ‘university’]
[‘RelatedTo’, ‘passman/n’, ‘university’]
[‘RelatedTo’, ‘semester’, ‘university’]
[‘RelatedTo’, ‘sophomore/n’, ‘university’]
[‘RelatedTo’, ‘state/n’, ‘university’]
[‘RelatedTo’, ‘studenty/a’, ‘university’]
[‘RelatedTo’, ‘tenure’, ‘university’]
[‘RelatedTo’, ‘town_and_gown/n’, ‘university’]
[‘RelatedTo’, ‘undergraduate’, ‘university’]
[‘RelatedTo’, ‘university’, ‘another’]
[‘RelatedTo’, ‘university’, ‘big_city’]
[‘RelatedTo’, ‘university’, ‘city’]
[‘RelatedTo’, ‘university’, ‘graduate_school’]
[‘RelatedTo’, ‘university’, ‘professor’]
[‘RelatedTo’, ‘university’, ‘than’]
[‘RelatedTo’, ‘university’, ‘you_verse’]
[‘RelatedTo’, ‘universitylike/a’, ‘university’]
[‘RelatedTo’, ‘ut’, ‘university’]
[‘TranslationOf’, ‘/InstanceOf/,/c/en/kyushi_university’, ‘university’]
[‘TranslationOf’, ‘/IsA/,/c/en/pohang_university’, ‘university’]
[‘TranslationOf’, ‘/LocatedNear/,/c/en/professor’, ‘university’]
[‘UsedFor’, ‘university’, ‘education_gain_of_knowledge’]
[‘UsedFor’, ‘university’, ‘relaxation’]
[‘UsedFor’, ‘university’, ‘study’]
[‘UsedFor’, ‘university’, ‘study_experiment’]
Files: 3 Total Assertions: 3321406 English_assertions 2133278
[‘AtLocation’, ‘argument_about_idea’, ‘university’]
[‘AtLocation’, ‘bookstore’, ‘university’]
[‘AtLocation’, ‘build’, ‘university’]
[‘AtLocation’, ‘cotton_fiber’, ‘university’]
[‘AtLocation’, ‘drug’, ‘university’]
[‘AtLocation’, ‘education’, ‘university’]
[‘AtLocation’, ‘freedom_of_think’, ‘university’]
[‘AtLocation’, ‘front_room’, ‘university’]
[‘AtLocation’, ‘girl’, ‘university’]
[‘AtLocation’, ‘hydrogen_and_oxygen’, ‘university’]
[‘AtLocation’, ‘laboratory’, ‘university’]
[‘AtLocation’, ‘mozart’, ‘university’]
[‘AtLocation’, ‘not_you’, ‘university’]
[‘AtLocation’, ‘orbit’, ‘university’]
[‘AtLocation’, ‘outerspace’, ‘university’]
[‘AtLocation’, ‘paper’, ‘university’]
[‘AtLocation’, ‘politics’, ‘university’]
[‘AtLocation’, ‘psychology’, ‘university’]
[‘AtLocation’, ‘security’, ‘university’]
[‘AtLocation’, ‘university’, ‘city’]
[‘AtLocation’, ‘university’, ‘florida’]
[‘AtLocation’, ‘wild_college_girl’, ‘university’]
[‘CapableOf’, ‘university’, ‘require_study’]
[‘DefinedAs’, ‘university’, ‘plural_of_university’]
[‘EtymologicallyDerivedFrom’, ‘moo_u’, ‘university’]
[‘EtymologicallyDerivedFrom’, ‘nonuniversity’, ‘university’]
[‘EtymologicallyDerivedFrom’, ‘preuniversity’, ‘university’]
[‘InstanceOf’, ‘mit’, ‘university’]
[‘IsA’, ‘university’, ‘large_school’]
[‘IsA’, ‘university’, ‘place_of_intellectual_freedom’]
[‘IsA’, ‘university’, ‘school_of_high_educatin’]
[‘PartOf’, ‘university_department’, ‘university’]
[‘RelatedTo’, ‘brain_farm/n’, ‘university’]
[‘RelatedTo’, ‘commence/v’, ‘university’]
[‘RelatedTo’, ‘complex/n’, ‘university’]
[‘RelatedTo’, ‘compound/n’, ‘university’]
[‘RelatedTo’, ‘csu’, ‘university’]
[‘RelatedTo’, ‘don/n’, ‘university’]
[‘RelatedTo’, ‘duke’, ‘university’]
[‘RelatedTo’, ‘fresher_flu/n’, ‘university’]
[‘RelatedTo’, ‘gender-blind/a’, ‘university’]
[‘RelatedTo’, ‘graduate_engineer/n’, ‘university’]
[‘RelatedTo’, ‘holiday/n’, ‘university’]
[‘RelatedTo’, ‘honor_roll/n’, ‘university’]
[‘RelatedTo’, ‘interuniversity/a’, ‘university’]
[‘RelatedTo’, ‘ivy_league/n’, ‘university’]
[‘RelatedTo’, ‘magnifico/n’, ‘university’]
[‘RelatedTo’, ‘plate-glass_university/n’, ‘university’]
[‘RelatedTo’, ‘privatdozent/n’, ‘university’]
[‘RelatedTo’, ‘professor’, ‘university’]
[‘RelatedTo’, ‘reader/n’, ‘university’]
[‘RelatedTo’, ‘registrar/n’, ‘university’]
[‘RelatedTo’, ‘school/n’, ‘university’]
[‘RelatedTo’, ‘semester_hour/n’, ‘university’]
[‘RelatedTo’, ‘student’, ‘university’]
[‘RelatedTo’, ‘summer_school/n’, ‘university’]
[‘RelatedTo’, ‘tutorial/n’, ‘university’]
[‘RelatedTo’, ‘u’, ‘university’]
[‘RelatedTo’, ‘university’, ‘build’]
[‘RelatedTo’, ‘varsity/n’, ‘university’]
[‘Synonym’, ‘college/n’, ‘university’]
[‘TranslationOf’, ‘/IsA/,/c/en/korea_university’, ‘university’]
[‘TranslationOf’, ‘/PartOf/,/c/en/department’, ‘university’]
[‘UsedFor’, ‘university’, ‘sit_on_it’]
Files: 4 Total Assertions: 4983568 English_assertions 3200027
[‘Antonym’, ‘university’, ‘primary’]
[‘AtLocation’, ‘ball_point_pen’, ‘university’]
[‘AtLocation’, ‘boy’, ‘university’]
[‘AtLocation’, ‘bureaucracy’, ‘university’]
[‘AtLocation’, ‘cold’, ‘university’]
[‘AtLocation’, ‘concert_hall’, ‘university’]
[‘AtLocation’, ‘dean’, ‘university’]
[‘AtLocation’, ‘exam_table’, ‘university’]
[‘AtLocation’, ‘graduate_student’, ‘university’]
[‘AtLocation’, ‘intellectual_freedom’, ‘university’]
[‘AtLocation’, ‘lecture_theatre’, ‘university’]
[‘AtLocation’, ‘noon’, ‘university’]
[‘AtLocation’, ‘rock’, ‘university’]
[‘AtLocation’, ‘someone’, ‘university’]
[‘AtLocation’, ‘system_engineer_department’, ‘university’]
[‘AtLocation’, ‘textbook’, ‘university’]
[‘AtLocation’, ‘theater_hall’, ‘university’]
[‘AtLocation’, ‘think’, ‘university’]
[‘AtLocation’, ‘ufo’, ‘university’]
[‘CapableOf’, ‘university’, ‘raise_it_admission_standard’]
[‘InstanceOf’, ‘kyushi_university’, ‘university’]
[‘IsA’, ‘university’, ‘bar’]
[‘IsA’, ‘university’, ‘educational_facility’]
[‘IsA’, ‘university’, ‘hospital’]
[‘IsA’, ‘university’, ‘institution’]
[‘IsA’, ‘university’, ‘unnatural_thing’]
[‘RelatedTo’, ‘alumna/n’, ‘university’]
[‘RelatedTo’, ‘aula_magna/n’, ‘university’]
[‘RelatedTo’, ‘common_room/n’, ‘university’]
[‘RelatedTo’, ‘course’, ‘university’]
[‘RelatedTo’, ‘dean_list/n’, ‘university’]
[‘RelatedTo’, ‘degree/n’, ‘university’]
[‘RelatedTo’, ‘doctor/n’, ‘university’]
[‘RelatedTo’, ‘folkstyle/a’, ‘university’]
[‘RelatedTo’, ‘fraternity’, ‘university’]
[‘RelatedTo’, ‘freshman/n’, ‘university’]
[‘RelatedTo’, ‘gymnasium/n’, ‘university’]
[‘RelatedTo’, ‘hall/n’, ‘university’]
[‘RelatedTo’, ‘hall_of_residence/n’, ‘university’]
[‘RelatedTo’, ‘harvard/n’, ‘university’]
[‘RelatedTo’, ‘inceptor/n’, ‘university’]
[‘RelatedTo’, ‘kasetsart/n’, ‘university’]
[‘RelatedTo’, ‘low_ivy/n’, ‘university’]
[‘RelatedTo’, ‘lsu’, ‘university’]
[‘RelatedTo’, ‘main_build/n’, ‘university’]
[‘RelatedTo’, ‘principal/n’, ‘university’]
[‘RelatedTo’, ‘sabbatical/n’, ‘university’]
[‘RelatedTo’, ‘sorbonne/n’, ‘university’]
[‘RelatedTo’, ‘space’, ‘university’]
[‘RelatedTo’, ‘uni/n’, ‘university’]
[‘RelatedTo’, ‘universe/n’, ‘university’]
[‘RelatedTo’, ‘university’, ‘high_than’]
[‘RelatedTo’, ‘university’, ‘place’]
[‘RelatedTo’, ‘universitywide/a’, ‘university’]
[‘UsedFor’, ‘university’, ‘center_of_learn’]
[‘UsedFor’, ‘university’, ‘learn_thing_teach_thing_do_research’]
[‘UsedFor’, ‘university’, ‘specialize_learn’]
Files: 5 Total Assertions: 6644285 English_assertions 4266886
[‘AtLocation’, ‘bill_gate’, ‘university’]
[‘AtLocation’, ‘chair’, ‘university’]
[‘AtLocation’, ‘debate’, ‘university’]
[‘AtLocation’, ‘football_field’, ‘university’]
[‘AtLocation’, ‘gentleman’, ‘university’]
[‘AtLocation’, ‘object’, ‘university’]
[‘AtLocation’, ‘paper_clip’, ‘university’]
[‘AtLocation’, ‘physic’, ‘university’]
[‘AtLocation’, ‘science_laboratory’, ‘university’]
[‘AtLocation’, ‘space_shuttle’, ‘university’]
[‘AtLocation’, ‘tree’, ‘university’]
[‘AtLocation’, ‘veterinary_hospital’, ‘university’]
[‘AtLocation’, ‘your_butt’, ‘university’]
[‘HasSubevent’, ‘university’, ‘be_best_student’]
[‘IsA’, ‘university’, ‘place_for_learn_and_research’]
[‘IsA’, ‘university’, ‘special_kind_of_school_to_learn_enough_to_get_good_job’]
[‘PartOf’, ‘university’, ‘house’]
[‘RelatedTo’, ‘academy/n’, ‘university’]
[‘RelatedTo’, ‘bursary/n’, ‘university’]
[‘RelatedTo’, ‘business’, ‘university’]
[‘RelatedTo’, ‘clear/n’, ‘university’]
[‘RelatedTo’, ‘college/n’, ‘university’]
[‘RelatedTo’, ‘communiversity/n’, ‘university’]
[‘RelatedTo’, ‘convenor/n’, ‘university’]
[‘RelatedTo’, ‘curriculum/n’, ‘university’]
[‘RelatedTo’, ‘diploma_mill/n’, ‘university’]
[‘RelatedTo’, ‘docent/n’, ‘university’]
[‘RelatedTo’, ‘exhibition/n’, ‘university’]
[‘RelatedTo’, ‘finalist/n’, ‘university’]
[‘RelatedTo’, ‘fiu’, ‘university’]
[‘RelatedTo’, ‘gap_year/n’, ‘university’]
[‘RelatedTo’, ‘intervarsity/n’, ‘university’]
[‘RelatedTo’, ‘junior/a’, ‘university’]
[‘RelatedTo’, ‘major/n’, ‘university’]
[‘RelatedTo’, ‘matriculate/v’, ‘university’]
[‘RelatedTo’, ‘minor/n’, ‘university’]
[‘RelatedTo’, ‘minor/v’, ‘university’]
[‘RelatedTo’, ‘nottingham/n’, ‘university’]
[‘RelatedTo’, ‘numerus_clausus/n’, ‘university’]
[‘RelatedTo’, ‘rag/v’, ‘university’]
[‘RelatedTo’, ‘rector/n’, ‘university’]
[‘RelatedTo’, ‘safety_school/n’, ‘university’]
[‘RelatedTo’, ‘tufthunter/n’, ‘university’]
[‘RelatedTo’, ‘tuition/n’, ‘university’]
[‘RelatedTo’, ‘ucca’, ‘university’]
[‘RelatedTo’, ‘um’, ‘university’]
[‘RelatedTo’, ‘universal/a’, ‘university’]
[‘RelatedTo’, ‘university’, ‘adult_school’]
[‘RelatedTo’, ‘university’, ‘another_college’]
[‘RelatedTo’, ‘university’, ‘learn’]
[‘RelatedTo’, ‘university’, ‘nice’]
[‘RelatedTo’, ‘university’, ‘verse’]
[‘TranslationOf’, ‘/IsA/,/c/en/korea_university’, ‘university’]
[‘UsedFor’, ‘university’, ‘eat’]
[‘UsedFor’, ‘university’, ‘research’]
Files: 6 Total Assertions: 8305649 English_assertions 5334937
[‘AtLocation’, ‘bomb’, ‘university’]
[‘AtLocation’, ‘drunk_student’, ‘university’]
[‘AtLocation’, ‘flower_garden’, ‘university’]
[‘AtLocation’, ‘geology’, ‘university’]
[‘AtLocation’, ‘history_book’, ‘university’]
[‘AtLocation’, ‘intellegent_professor’, ‘university’]
[‘AtLocation’, ‘parkink_lot’, ‘university’]
[‘AtLocation’, ‘pencil’, ‘university’]
[‘AtLocation’, ‘scholar’, ‘university’]
[‘AtLocation’, ‘see_associate_professor’, ‘university’]
[‘CapableOf’, ‘university’, ‘consist_of_several_college’]
[‘HasSubevent’, ‘university’, ‘learn_new_knowladges’]
[‘IsA’, ‘university’, ‘organization/n’]
[‘IsA’, ‘university’, ‘place_where_go_student’]
[‘IsA’, ‘university’, ‘where_person_learn’]
[‘LocationOfAction’, ‘see_associate_professor’, ‘university’]
[‘LocationOfAction’, ‘see_professor’, ‘university’]
[‘ReceivesAction’, ‘university’, ‘populate_by_student’]
[‘RelatedTo’, ‘aulic/n’, ‘university’]
[‘RelatedTo’, ‘bu’, ‘university’]
[‘RelatedTo’, ‘calculus’, ‘university’]
[‘RelatedTo’, ‘common/n’, ‘university’]
[‘RelatedTo’, ‘frat_house/n’, ‘university’]
[‘RelatedTo’, ‘fresher_week/n’, ‘university’]
[‘RelatedTo’, ‘graduate’, ‘university’]
[‘RelatedTo’, ‘hood/n’, ‘university’]
[‘RelatedTo’, ‘intercampus/a’, ‘university’]
[‘RelatedTo’, ‘lector/n’, ‘university’]
[‘RelatedTo’, ‘lecturer/n’, ‘university’]
[‘RelatedTo’, ‘postsecondary_school/n’, ‘university’]
[‘RelatedTo’, ‘psychology’, ‘university’]
[‘RelatedTo’, ‘questionist/n’, ‘university’]
[‘RelatedTo’, ‘rag/n’, ‘university’]
[‘RelatedTo’, ‘read_week/n’, ‘university’]
[‘RelatedTo’, ‘research’, ‘university’]
[‘RelatedTo’, ‘roommate/n’, ‘university’]
[‘RelatedTo’, ‘rusticate/v’, ‘university’]
[‘RelatedTo’, ‘school’, ‘university’]
[‘RelatedTo’, ‘senate/n’, ‘university’]
[‘RelatedTo’, ‘tufthunting/n’, ‘university’]
[‘RelatedTo’, ‘university’, ‘big’]
[‘RelatedTo’, ‘university’, ‘large’]
[‘RelatedTo’, ‘university’, ‘large_college’]
[‘RelatedTo’, ‘university’, ‘many_build’]
[‘TranslationOf’, ‘/AtLocation/,/c/en/graduate_student’, ‘university’]
Files: 7 Total Assertions: 9966902 English_assertions 6401463
[‘AtLocation’, ‘computer_lab’, ‘university’]
[‘AtLocation’, ‘computer_scientist’, ‘university’]
[‘AtLocation’, ‘degree’, ‘university’]
[‘AtLocation’, ‘large_library’, ‘university’]
[‘AtLocation’, ‘lizard’, ‘university’]
[‘AtLocation’, ‘musical_composition’, ‘university’]
[‘AtLocation’, ‘outer_space’, ‘university’]
[‘AtLocation’, ‘riverside_drive/n/windsor,_ontario’, ‘university’]
[‘AtLocation’, ‘science’, ‘university’]
[‘AtLocation’, ‘something’, ‘university’]
[‘AtLocation’, ‘sorority_house’, ‘university’]
[‘AtLocation’, ‘study’, ‘university’]
[‘CapableOf’, ‘university’, ‘honor_researcher_with_award’]
[‘DefinedAs’, ‘university’, ‘last_school_student_attend’]
[‘EtymologicallyDerivedFrom’, ‘interuniversity’, ‘university’]
[‘EtymologicallyDerivedFrom’, ‘university_of_life’, ‘university’]
[‘EtymologicallyDerivedFrom’, ‘universitywide’, ‘university’]
[‘HasA’, ‘university’, ‘become_much_like_factory’]
[‘HasSubevent’, ‘university’, ‘have_new_friend’]
[‘IsA’, ‘university’, ‘dwell’]
[‘IsA’, ‘university’, ‘educational_institution’]
[‘LocationOfAction’, ‘study’, ‘university’]
[‘RelatedTo’, ‘bejan/n’, ‘university’]
[‘RelatedTo’, ‘bursar/n’, ‘university’]
[‘RelatedTo’, ‘campus/n’, ‘university’]
[‘RelatedTo’, ‘civilian/n’, ‘university’]
[‘RelatedTo’, ‘degree_mill/n’, ‘university’]
[‘RelatedTo’, ‘degreelessness/n’, ‘university’]
[‘RelatedTo’, ‘dormitory’, ‘university’]
[‘RelatedTo’, ‘facebook/n’, ‘university’]
[‘RelatedTo’, ‘gaysoc/n’, ‘university’]
[‘RelatedTo’, ‘honour_roll/n’, ‘university’]
[‘RelatedTo’, ‘massachusetts_institute_of_technology/n’, ‘university’]
[‘RelatedTo’, ‘moo_u/n’, ‘university’]
[‘RelatedTo’, ‘ph.d/n’, ‘university’]
[‘RelatedTo’, ‘prep_school/n’, ‘university’]
[‘RelatedTo’, ‘proctor/n’, ‘university’]
[‘RelatedTo’, ‘secondary_education/n’, ‘university’]
[‘RelatedTo’, ‘send_down/v’, ‘university’]
[‘RelatedTo’, ‘sorority/n’, ‘university’]
[‘RelatedTo’, ‘stanford/n’, ‘university’]
[‘RelatedTo’, ‘university’, ‘after_school’]
[‘RelatedTo’, ‘university’, ‘college_or’]
[‘RelatedTo’, ‘university’, ‘high’]
[‘RelatedTo’, ‘university’, ‘like_college’]
[‘Synonym’, ‘school/n/institution_dedicated_to_teaching_and_learning’, ‘university’]
[‘TranslationOf’, ‘/AtLocation/,/c/en/system_engineer_department’, ‘university’]
[‘UsedFor’, ‘university’, ‘hub_of_think’]
[‘UsedFor’, ‘university’, ‘learn’]

[‘AtLocation’, ‘college’, ‘big_city’]
[‘AtLocation’, ‘college’, ‘city’]
[‘AtLocation’, ‘college’, ‘disrepair’]
[‘AtLocation’, ‘pen’, ‘college’]
[‘AtLocation’, ‘student’, ‘college’]
[‘CapableOf’, ‘college’, ‘honor_alumnus_with_award’]
[‘DefinedAs’, ‘college’, ‘high_level_of_school’]
[‘EtymologicallyDerivedFrom’, ‘collegebound’, ‘college’]
[‘EtymologicallyDerivedFrom’, ‘collegelike’, ‘college’]

[‘RelatedTo’, ‘accept’, ‘college’]
[‘RelatedTo’, ‘bar’, ‘college’]
[‘RelatedTo’, ‘botany’, ‘college’]
[‘RelatedTo’, ‘class’, ‘college’]
[‘RelatedTo’, ‘college’, ‘big’]
[‘RelatedTo’, ‘college’, ‘big_school’]
[‘RelatedTo’, ‘college’, ‘class’]
[‘RelatedTo’, ‘college’, ‘continue’]
[‘RelatedTo’, ‘college’, ‘facility’]
[‘RelatedTo’, ‘college’, ‘for_senior’]
[‘RelatedTo’, ‘college’, ‘four_year’]
[‘RelatedTo’, ‘college’, ‘graduation’]
[‘RelatedTo’, ‘college’, ‘high_learn’]
[‘RelatedTo’, ‘college’, ‘high_school’]
[‘RelatedTo’, ‘college’, ‘junior’]
[‘RelatedTo’, ‘college’, ‘place_learn’]
[‘RelatedTo’, ‘college’, ‘post’]
[‘RelatedTo’, ‘college’, ‘secondary’]
[‘RelatedTo’, ‘college’, ‘student_teacher’]
[‘RelatedTo’, ‘college’, ‘two_year’]
[‘RelatedTo’, ‘college’, ‘university’]
[‘RelatedTo’, ‘college’, ‘young’]
[‘RelatedTo’, ‘colleger/n’, ‘college’]
[‘RelatedTo’, ‘collegial/a’, ‘college’]
[‘RelatedTo’, ‘day_release/n’, ‘college’]
[‘RelatedTo’, ‘doctor/n’, ‘college’]
[‘RelatedTo’, ‘foundationer/n’, ‘college’]
[‘RelatedTo’, ‘hall’, ‘college’]
[‘RelatedTo’, ‘honor_roll/n’, ‘college’]
[‘RelatedTo’, ‘intercampus/a’, ‘college’]
[‘RelatedTo’, ‘intercollege/a’, ‘college’]
[‘RelatedTo’, ‘matriculate/v’, ‘college’]
[‘RelatedTo’, ‘philosophy’, ‘college’]
[‘RelatedTo’, ‘precollegiate/a’, ‘college’]
[‘RelatedTo’, ‘sadie_hawkins_dance/n’, ‘college’]
[‘RelatedTo’, ‘scholar/n’, ‘college’]
[‘RelatedTo’, ‘semester’, ‘college’]
[‘RelatedTo’, ‘waithood/n’, ‘college’]
[‘RelatedTo’, ‘year/n’, ‘college’]
[‘UsedFor’, ‘college’, ‘get_away_from_parent’]
[‘UsedFor’, ‘college’, ‘person_that_do_not_work’]
[‘UsedFor’, ‘college’, ‘relaxation’]

[‘AtLocation’, ‘college’, ‘airport’]
[‘AtLocation’, ‘college’, ‘house’]
[‘AtLocation’, ‘college’, ‘town_or_city’]
[‘AtLocation’, ‘food’, ‘college’]
[‘AtLocation’, ‘snake’, ‘college’]
[‘AtLocation’, ‘student_in_registration_booth’, ‘college’]
[‘CapableOf’, ‘college’, ‘honor_student_with_degree’]
[‘HasProperty’, ‘college’, ‘expensive’]
[‘HasProperty’, ‘college’, ‘specialize_in_specific_topic’]

‘RelatedTo’, ‘alumnus_association/n’, ‘college’]
[‘RelatedTo’, ‘art’, ‘college’]
[‘RelatedTo’, ‘as_level/n’, ‘college’]
[‘RelatedTo’, ‘auditorium’, ‘college’]
[‘RelatedTo’, ‘aularian/n’, ‘college’]
[‘RelatedTo’, ‘board/n’, ‘college’]
[‘RelatedTo’, ‘cao’, ‘college’]
[‘RelatedTo’, ‘civilian/n’, ‘college’]
[‘RelatedTo’, ‘college’, ‘after’]
[‘RelatedTo’, ‘college’, ‘after_graduation’]
[‘RelatedTo’, ‘college’, ‘campus’]
[‘RelatedTo’, ‘college’, ‘department’]
[‘RelatedTo’, ‘college’, ‘ed’]
[‘RelatedTo’, ‘college’, ‘education_build’]
[‘RelatedTo’, ‘college’, ‘education_place’]
[‘RelatedTo’, ‘college’, ‘educational’]
[‘RelatedTo’, ‘college’, ‘far_education’]
[‘RelatedTo’, ‘college’, ‘grad’]
[‘RelatedTo’, ‘college’, ‘institute’]
[‘RelatedTo’, ‘college’, ‘like_school’]
[‘RelatedTo’, ‘college’, ‘many_person’]
[‘RelatedTo’, ‘college’, ‘party’]
[‘RelatedTo’, ‘college’, ‘party_class’]
[‘RelatedTo’, ‘college’, ‘post_secondary’]
[‘RelatedTo’, ‘college’, ‘student_class’]
[‘RelatedTo’, ‘college’, ‘teacher’]
[‘RelatedTo’, ‘college’, ‘tertiary_education’]
[‘RelatedTo’, ‘college’, ‘two’]
[‘RelatedTo’, ‘college’, ‘university_department’]
[‘RelatedTo’, ‘college’, ‘university_part’]
[‘RelatedTo’, ‘collegewide/a’, ‘college’]
[‘RelatedTo’, ‘common/n’, ‘college’]
[‘RelatedTo’, ‘election’, ‘college’]
[‘RelatedTo’, ‘faculty/n’, ‘college’]
[‘RelatedTo’, ‘frat_house/n’, ‘college’]
[‘RelatedTo’, ‘institute’, ‘college’]
[‘RelatedTo’, ‘keg’, ‘college’]
[‘RelatedTo’, ‘learn’, ‘college’]
[‘RelatedTo’, ‘lodge/n’, ‘college’]
[‘RelatedTo’, ‘move’, ‘college’]
[‘RelatedTo’, ‘perendinate/v’, ‘college’]
[‘RelatedTo’, ‘postcollege/a’, ‘college’]
[‘RelatedTo’, ‘postcollegiate/a’, ‘college’]
[‘RelatedTo’, ‘professor’, ‘college’]
[‘RelatedTo’, ‘quiz_bowl/n’, ‘college’]
[‘RelatedTo’, ‘safety_school/n’, ‘college’]
[‘RelatedTo’, ‘school’, ‘college’]
[‘RelatedTo’, ‘school/n’, ‘college’]
[‘RelatedTo’, ‘sophomore/n’, ‘college’]
[‘Synonym’, ‘university/n’, ‘college’]
[‘UsedFor’, ‘college’, ‘live_in’]
[‘UsedFor’, ‘college’, ‘meet_person’]

There were many thousands of other knowledge triples (relationship concept1 concept2).

CFP @ HICSS 49: Smart Service Systems: Analytics, Cognition and Innovation Minitrack

Dear Colleagues,

Hello! We are serving as co-chairs of the “Smart Service Systems: Analytics, Cognition and Innovation (http://www.hicss.org/#!smart-service-systems/c1mcg)” minitrack in the Decision Analytics, Mobile Services and Service Science Track of the upcoming 49th Hawaii International Conference on System Sciences (HICSS) (http://www.hicss.org/). We are writing to scholars such as you with expertise in various areas of service systems, analytics, innovation, mobile systems and cognition in hopes that you will consider submitting a paper to our minitrack. The deadline for submitting papers to HICSS-49 is June 15, 2015. Please consider submitting your work if it is related to any of the specific topics listed and/or if you feel it addresses visions of the future of this track. We expect a range of concepts, tools, methods, philosophies and theories to be discussed. We thank you, in advance, for your valuable contribution to HICSS-49. Please let us know if you have any questions or need additional information. We look forward to receiving your submission!

Best Regards,

 CALL FOR PAPERS for HICSS-49

Hawaii International Conference on System Sciences

Additional detail may be found on HICSS primary web site: (http://www.hicss.org/)

Smart service systems can be characterized by: (1) the types of offerings to their customers and/or citizens, (2) the types of jobs or roles for people within them, and (3) the types of returns they offer investors interested in growth and development, through improved use of technology, talent, or organizational and governance forms, which create (dis)incentives that (re)shape behaviors. An important trend in smart service systems is the increasing availability of cognitive assistants (e.g., Siri, Watson, Jibo, Echo, etc.) to boost productivity and creativity of all the people inside them. There is a need to apply robust research findings in the appropriate management and organizational contexts related to innovation of smart service systems, service innovation, quality, architecture, design and delivery, and the resulting customer satisfaction and business value. In part, because of analytics and cognitive systems, smart service systems adapt to a constantly changing environment to benefit customers and providers. Using big data analytics, service providers try to compete for customers by (1) improving existing offerings to customers, (2) innovating new types of offerings, (3) evolving their portfolio of offerings and making better recommendations to customers, (4) changing their relationships to suppliers and others in the ecosystem in ways their customers perceive as more sustainable, fair, or responsible.

The goal of this track is to explore the challenges, issues and opportunities related to innovation of smart service systems that enable value co-creation with analytics, cognitive and human systems. We are interested in novel theories, approaches and applications for innovation of smart service systems. Possible topics of applied, field and empirical research include, but are not limited to:

  • Theories, approaches and applications for innovation of smart service systems
  • Value co-creation processes, metrics and analytics for smart innovation processes
  • Methods scale the benefits of new knowledge globally, rapidly, and profitably
  • Service-oriented agile IT realization platform for smart service co-creation
  • Place of cognitive systems, computing, system engineering, cloud for smart service systems
  • Innovation ecosystems with internet and internet-of-things
  • Theories and approaches for integrating analytical and intuitive thinking processes
  • Open innovation and social responsibility
  • Planning, building and managing design and innovation infrastructures and platforms
  • Technology and organizational platforms support rapid scaling processes (smart phones, franchises, etc.)
  • Smart service systems include the customer, provider, and other entities as sources of capabilities, resources, demand, constraints, rights, responsibilities in value co-creation processes, and includes current applications of human and cognitive systems
  • Analytics models, tools and engine for analytics support
  • Agile business development platform for operational enablement: business processes, rules, real-time event management
  • The commoditization of business processes (e.g. out-tasking, ITIL, SCORE), software (e.g. the software-as-service model, software oriented architecture, application service providers) and hardware (e.g., on-demand, utility computing, cloud computing, software oriented infrastructure with virtualized resources, infrastructure service providers for innovations
  • Self-service and smart technologies & management for sustainable innovations
  • Services implications to value chains, networks, constellations and shops
  • Collaborative innovation management in B2B and B2C e-commerce

Important Deadlines

  • June 15 – Submit full manuscripts for review. The review is double-blind; therefore this submission must be without author names. How and when to submit a paper http://www.hicss.org/#!call-for-papers/c1cd9
  • Receive acceptance notification by August 16.
  • Revise your manuscript to add author names. If required, make other changes.
  • Submit Final Paper for Publication by September 15.

Defining Service Innovation

A colleague recently asked – what is service innovation?

OECD and others have written a lot about service innovation from a largely economic perspective, contrasted with agricultural or manufacturing innovation.

http://www.oecd.org/sti/inno/innovationinservicestheroleofrdandrdpoliciesinnoserv.htm

The biggest challenge in defining service and service innovation are the dominant logics – which is usually based on economics and sectors of the economy:

product innovation – a thing

process innovation – a set of activities

service innovation – a system with people inside

well aren’t there things and activities in systems with people inside?

so what’s the difference?

Here is the most concise I can be:

service is defined as the application of knowledge for mutual benefits (value co-creation)

service innovations scale the benefits of new knowledge, globally, rapidly, and sustainably

service platforms help scale service innovations – platforms can be:
technology: Internet, smart phones
business models: franchises, cartels
government policy and rules: universal education, universal access

Call for Action: A new community of interest focused on service economic models, measures and impacts

Dear colleagues,

ISSIP (International Society of Service Innovation Professionals, http://www.issip.org/) is creating a community of interest focused on service economic models, measures and impacts. The group will start with bi-monthly calls with guest speakers stimulating the conversation and helping to prioritize action and content creation. If you would like to participate contact:  Doug Morse at djmorse01@comcast.net

Please provide the following information:

  • Name
  • Affiliations (company /institution etc )
  • Email address – to be used for meeting notifications only
  • Do you want to present material on the subject (If so 25 word or less description)
  • Other roles you might want to play (participant only, content sharing etc.)
  • Best day of the week for calls and morning or afternoon (pacific time)

Overview / Summary: Underlying the global economy today is an economy driven by services. Globally, the monetary exchange for services now exceeds that of the combined manufacturing and agricultural sectors of the economy. Unfortunately the business valuations and managerial processes of today are still deeply rooted in the world that Adam Smith envisioned in 1776 in his book The Wealth of Nations. Consequently companies tend to focus on production optimization, supply chain optimization and efficient distribution channels much more than customer optimization and creating customer value. The difference in the modern economy is that the building of goods does not create value alone but by the outcomes that those goods might produce for those who purchase and use them. The wealth of nations is not about capital accumulation today but rather it is more driven by the consumption of knowledge and resources.

Why discuss and study Service Economics? If we do not change the core measures of how we measure business success and value, or key global economic drivers in a way that matches current realities, then we will not be able to influence changes in education, business behaviors or social change. For governments invest in research and education around services they must better understand how the economy works. Public universities still teach business process and economics as if we were dominated by a manufacturing economy. Service Innovation is inhibited by archaic economic measures and theories. ISSIP can bring together the communities to influence change through research, awareness and action.

Service Economics Group Charter / Mission: The key purpose Service Economics Group is to bring together a diverse team of individuals and organizations to help define and better understand current and desired future state economic tools, models, processes and technologies that would reduce inhibitors to current service innovation and to drive change that accelerate service innovation in the future. Ultimately the group would become an instigator / influencer of change to economic policies, economic and business metrics and accounting rules in support of the services economy.

This may include but is not limited to the following:

  • Create a center of knowledge and expertise around service economics
  • Use the COE ( Center of Expertise ) to drive change that promotes service innovation, new education models, public policy and economic models.
  • Understand new forms of value creation
    • Customer Equity – Customers as an asset – beyond ‘goodwill’
    • Value of Data (big data, sensor data et al.)
    • Touchpoint value ( Twitter, Facebook, other social media that collects visits and views )
  • Research and education of both micro and macro-economic models of service(s)
  • Definition and valuations of non-tangible economic transactions
  • Create and disseminate intellectual property (papers, books, presentations etc.) that create a better understanding of services related economics

Doug Morse, Founder/Chief Inspiration Officer at ServTrans (www.linkedin.com/in/dougmorse/en)

Stephen Kwan, Lucas Professor of Service Science & Associate Dean Lucas Graduate School of Business at San Jose State University (www.linkedin.com/pub/stephen-kwan/11/669/871/en)

IBM’s Cognitive Systems Institute Group (CSIG)

As background on IBM’s broader interests and to summarize IBM’s Cognitive Systems Institute Group (CSIG):

(1) over the next decade cognitive assistants will begin appearing for all occupations, job tasks, and in many languages

(2) globally, this creates the potential for tens of thousands of startups to build and deploy these assistants, and improve them over time

(3) to get the skills and build these systems – IBM will be encouraging student Hackathons on Bluemix

(4) IBM is collaborating with faculty to increase the quantity and quality of cognitive computing componentry on Bluemix

You can learn about Bluemix here:
http://ibm.biz/LearnBluemix

How to get started with Bluemix

Notice the references to Watson, and Weka at the above URL (and in the attached png).

IBM GUP (Global University Programs) wants to make awards to faculty who will help us with the ambitious CSIG mission. A mission that will take a decade or more to realize.

To continue to summarize IBM’s Cognitive Systems Institute Group (CSIG):

(5) IBM is collaborating with faculty to submit IBM aligned grant proposals to government and foundation funding agencies

(6) IBM is encouraging government and foundations to increase funding in this area

(7) Boosting the creativity and productivity of people will increase GDP of nations and revenue-per-employee of companies

(8) When everyone can afford an executive assistant and personal coach, quality of life in smart service systems will be improved

(9) This is consistent with IBM’s vision is of a Smarter Planet, that is built-with-IBM.

(10) The cognitive era will transform industries and professions, as “cognition as a service” enables “IBM as a service” to our customers, partners, and employees.

It is easy to get involved in CSIG, and we ask people to start by joining the LinkedIn discussion – see below.

Additional pointers:
CSIG on Linked In – https://www.linkedin.com/groups/Cognitive-Systems-Institute-6729452
Summary of other useful links: https://www.linkedin.com/groups/Its-easy-get-involved-CSIG-6729452.S.5970937409846665220
On-line directory of occupations, task: http://www.onetonline.org/
IBM Cognitive Awardees – http://cognitive-science.info/award-recipients/
Summary presentation: http://www.slideshare.net/spohrer/cognitive-20140912-v3
Weekly speaker series: http://cognitive-science.info/community/weekly-update/
About IBM University Programs: http://www.ibm.com/university

Please let me know if you have any questions.

It is easy to get involved in CSIG

CSIG = Cognitive Systems Institute Group

Mission: cognitive assistants for all occupations in smart service systems.
http://www.slideshare.net/spohrer/cognitive-20140912-v3

Join the CSIG LinkedIn discussions for more updates, pointers, and to see what others are doing
https://www.linkedin.com/groups/Cognitive-Systems-Institute-6729452

Ask about teaching a course with Watson – Watson University Programs
http://www.ibm.com/smarterplanet/us/en/ibmwatson/academic.html

Try IBM Watson Services on Bluemix
https://ace.ng.bluemix.net/#/solutions/solution=watson

Try IBM Watson Analytics on your data
http://www.ibm.com/analytics/watson-analytics/

Learn about the Cognitive Systems Institute Group (CSIG) community, challenges, awards and information resources here:
http://cognitive-science.info
Tweet with hashtag #Cognitive2.0 to send items to the website

Try Bluemix – register here
http://ibm.biz/HackBluemix

Try Bluemix – learn and access Watson services and Weka, open machine learning services
http://ibm.biz/LearnBluemix
More Bluemix component award categories coming (scroll to bottom)

CSIG helps identify funding for cognitive assistants for all occupations in smarter service systems:
http://www.nsf.gov/pubs/2014/nsf14610/nsf14610.htm
Try out O*NET here – type in an occupation (e.g., “biochemist”)
http://www.onetonline.org/

Download O*NET descriptions of nearly 1000 occupations
http://www.onetcenter.org/database.html?p=2

FYI: U Tronto Students Prototype a Watson Paralegal Cognitive Assistant
http://metronews.ca/news/toronto/1230021/watson-challenge-winners-at-u-of-t-want-to-create-a-great-canadian-company/
In 2014, ten universities taught with Watson, in 2015 nearly 100 will teach with Watson
Student projects are building a prototype and business plan for a company that is part of the Watson Ecosystem

Some cognitive systems gaps and challenges here:
http://cognitive-science.info/research-challenges/

For more information contact your regional IBM lead:
http://www.ibm.com/university

IBM CSIG: Cognitive Systems Institute Group

IBM established CSIG (Cognitive Systems Institute Group) to help faculty and students interested in learning more about the era of cognitive computing, and IBM’s platforms for teaching, research, and application development 0f cognitive components, systems, and applications.

It is easy to get involved in CSIG:

https://www.linkedin.com/groups/It-is-easy-get-involved-6729452.S.5955396461716844547

 

Also check out this website, for CSIG information and resource sharing:

Good online service blueprinting tools?

Does anyone know of any good online service blueprinting tools?

Looking for something simple to capture basic service systems information, for example:

For example:
Name of Service System: _______________________  
Roles:   ________________________________________
Props:  _________________________________________
Sequence:  _____________________________________

In artificial intelligence research, Schank and Abelson referred to this as Scripts:

See script theory: http://www.instructionaldesign.org/theories/script-theory.html
For example, this is the type of information that would be gathered:

Name of Service System: _______________________  
Restaurant

Roles:   ________________________________________
Diner, Hostess, Waitress, Chef, Server, Clearer, Cashier

Props:  _________________________________________
Building, Entry_Area, Dining_Room, Kitchen, Table, Chair, Menu, Tablecloth, Utensils, Salt_and_Pepper_Shakers, Food, Glass,Water, Credit_Card, Tip

Sequence:  _____________________________________
Diner enters Restaurant                        
Hostess seats Diner at table in chair                        
Diner reviews Menu and makes selection                        
Waitress arrives and takes drink order
Waitress bring drink and bread_basket
Waitress takes order                        
Waitress gives order to Chef                        
Chef cooks order and places food on plate                        
Diner drinks water
Diner eats bread
Servers takes food to table
Server refills glass of water
Diner places napkin in lap
Diner picks up utensil
Diner tastes food
Dinner seasons food with Salt_and_Pepper_Shakers                        
Diner eats food    
Waitress checks if everything is OK
Diner response everything is OK
Diner signals waitress he is finished                    
Waitress brings bill to table                        
Diner provides credit_card                        
Waitress takes credit_card to cashier                        
Cashier bills credit_card                        
Waitress returns credit_card to diner                        
Diner leaves tip                        
Diner leaves restaurant                        
Clearer clears table

From the previous post – many of MIT Concept Net 5 top ranked concepts are service systems – perhaps ISSIP.org – can add many new facts about service systems to this knowledge graph, if a service blueprinting tool allows such output:

[[‘place’, 458623], [‘person’, 372535], [‘company’, 35486], [‘town’, 33524], [‘educational_institution’, 32907], [‘airport’, 9858],  [‘stadium’, 6050],  [‘airline’, 2658],  [‘museum’, 2590], [‘community_group’, 2223], [‘hospital’, 2086], , [‘public_transit_system’, 2056], [‘non-profit_organisation’, 2052], ,[‘government_agency’, 1990], [‘shop_mall’, 1834], [‘trade_union’, 1274], , [‘non-profit_organization’, 1252], [‘municipality’, 1239], [‘home’, 1201], [‘power_station’, 1196], [‘family’, 1131], [‘sport_league’, 1116],  [‘state’, 1068],  [‘hotel’, 1054]

Or these:

[[‘place’, 458623], [‘person’, 372535], [‘populate_place’, 314554], [‘settlement’, 282695], [‘organisation’, 147159], ], [‘village’, 82999], [‘company’, 35486], [‘town’, 33524], [‘educational_institution’, 32907], [‘mean_of_transportation’, 31604], [‘administrative_region’, 27698], [‘populate_area’, 15714], [‘business’, 15284], [‘unite_state’, 15121],  [‘airport’, 9858], [‘organization’, 9776], [‘educational_organization’, 8820], [‘privately_hold_company’, 7548], [‘census-designated_place’, 6263], [‘california’, 6131], [‘stadium’, 6050], [‘private_school’, 3858], [‘new_york’, 3841], [‘khuzestan_province’, 3787], [‘country’, 3725], [‘canada’, 3550], [‘public_university’, 3432], , [‘unite_kingdom’, 3225], [‘china’, 2724], [‘airline’, 2658], [‘germany’, 2635], [‘museum’, 2590], [‘community_group’, 2223], [‘hospital’, 2086],  [‘private_university’, 2081], [‘public_transit_system’, 2056], [‘non-profit_organisation’, 2052], [‘village/n/united_states’, 2047], [‘government_agency’, 1990], [‘shop_mall’, 1834], [‘shop_center’, 1585], [‘house’, 1558], [‘trade_union’, 1274], , [‘non-profit_organization’, 1252], [‘municipality’, 1239], [‘home’, 1201], [‘power_station’, 1196], [‘family’, 1131],  [‘earth’, 1124], [‘sport_league’, 1116], [‘lighthouse’, 1092], [‘state’, 1068],  [‘hotel’, 1054]

Here are the 1054 knowledge triples for ‘hotel’ – there is lots of room for improvement:

[‘UsedFor’, ‘hotel’, ‘sleep’]
[‘UsedFor’, ‘hotel’, ‘sleep_and_shower’]
[‘UsedFor’, ‘hotel’, ‘sleep_overnight’]
[‘UsedFor’, ‘hotel’, ‘sleep_while_away_from_home’]
[‘UsedFor’, ‘hotel’, ‘stay_night_in_it’]
[‘UsedFor’, ‘hotel’, ‘rest’]
[‘UsedFor’, ‘hotel’, ‘hold_seminar’]
[‘UsedFor’, ‘hotel’, ‘place_to_get_some_food_while_travel’]
[‘UsedFor’, ‘hotel’, ‘place_to_rest_while_on_vacation’]
[‘UsedFor’, ‘hotel’, ‘stay_over’]
[‘HasA’, ‘hotel’, ‘maid_who_clean_room’]
[‘HasA’, ‘hotel’, ‘many_hotel_room’]
[‘HasA’, ‘hotel’, ‘swim_pool’]
[‘AtLocation’, ‘bellhop’, ‘hotel’]
[‘AtLocation’, ‘chair’, ‘hotel’]
[‘AtLocation’, ‘elevator’, ‘hotel’]
[‘AtLocation’, ‘food’, ‘hotel’]
[‘AtLocation’, ‘high_price’, ‘hotel’]
[‘AtLocation’, ‘hotel’, ‘touristic_area’]
[‘AtLocation’, ‘linux’, ‘hotel’]
[‘AtLocation’, ‘maid’, ‘hotel’]
[‘AtLocation’, ‘mouthwash’, ‘hotel’]
[‘AtLocation’, ‘pillow_case’, ‘hotel’]
[‘AtLocation’, ‘pool’, ‘hotel’]
[‘AtLocation’, ‘revolve_door’, ‘hotel’]
[‘AtLocation’, ‘room_key’, ‘hotel’]
[‘AtLocation’, ‘room_service’, ‘hotel’]
[‘AtLocation’, ‘something’, ‘hotel’]
[‘AtLocation’, ‘swim_pool’, ‘hotel’]
[‘AtLocation’, ‘terrace_rail’, ‘hotel’]
[‘AtLocation’, ‘wing’, ‘hotel’]
[‘NotHasA’, ‘mall’, ‘hotel’]
[‘RelatedTo’, ‘bellboy/n’, ‘hotel’]
[‘RelatedTo’, ‘boarder/n’, ‘hotel’]
[‘RelatedTo’, ‘boniface/n’, ‘hotel’]
[‘RelatedTo’, ‘capsule_hotel/n’, ‘hotel’]
[‘RelatedTo’, ‘chasseur/n’, ‘hotel’]
[‘RelatedTo’, ‘check-in/n’, ‘hotel’]
[‘RelatedTo’, ‘checkout/n’, ‘hotel’]
[‘RelatedTo’, ‘hotel’, ‘overnight_sleep’]
[‘RelatedTo’, ‘hotel’, ‘sleep_place’]
[‘RelatedTo’, ‘hotel’, ‘stay_overnight’]
[‘RelatedTo’, ‘hotel’, ‘temporary’]
[‘RelatedTo’, ‘house_detective/n’, ‘hotel’]
[‘RelatedTo’, ‘house_dick/n’, ‘hotel’]
[‘RelatedTo’, ‘motel/a’, ‘hotel’]
[‘RelatedTo’, ‘powder_room/n’, ‘hotel’]
[‘RelatedTo’, ‘resort’, ‘hotel’]
[‘RelatedTo’, ‘summer’, ‘hotel’]
[‘RelatedTo’, ‘twin/n’, ‘hotel’]
[‘RelatedTo’, ‘view’, ‘hotel’]
[‘UsedFor’, ‘hotel’, ‘store_person’]
[‘UsedFor’, ‘hotel’, ‘temporary_home’]
[‘AtLocation’, ‘bar_service’, ‘hotel’]
[‘AtLocation’, ‘book’, ‘hotel’]
[‘AtLocation’, ‘check_in_desk’, ‘hotel’]
[‘AtLocation’, ‘grind_floor’, ‘hotel’]
[‘AtLocation’, ‘hairdryer’, ‘hotel’]
[‘AtLocation’, ‘hotel’, ‘any_tropical_paradise_that_can_be_exploit’]
[‘AtLocation’, ‘laundry_room’, ‘hotel’]
[‘AtLocation’, ‘lobby’, ‘hotel’]
[‘AtLocation’, ‘sleep’, ‘hotel’]
[‘AtLocation’, ‘sofa_bed’, ‘hotel’]
[‘AtLocation’, ‘table’, ‘hotel’]
[‘AtLocation’, ‘taxi’, ‘hotel’]
[‘AtLocation’, ‘towel’, ‘hotel’]
[‘AtLocation’, ‘trash_can’, ‘hotel’]
[‘RelatedTo’, ‘check_in/v’, ‘hotel’]
[‘RelatedTo’, ‘check_out/v’, ‘hotel’]
[‘RelatedTo’, ‘dine_room/n’, ‘hotel’]
[‘RelatedTo’, ‘fonduk/n’, ‘hotel’]
[‘RelatedTo’, ‘hall’, ‘hotel’]
[‘RelatedTo’, ‘hotel’, ‘commercial’]
[‘RelatedTo’, ‘hotel’, ‘fancy’]
[‘RelatedTo’, ‘hotel’, ‘holiday’]
[‘RelatedTo’, ‘hotel’, ‘resort’]
[‘RelatedTo’, ‘hotel’, ‘stay_there’]
[‘RelatedTo’, ‘hotel’, ‘tourist_city’]
[‘RelatedTo’, ‘hotelward/r’, ‘hotel’]
[‘RelatedTo’, ‘passkey/n’, ‘hotel’]
[‘RelatedTo’, ‘resort_fee/n’, ‘hotel’]
[‘RelatedTo’, ‘twin_room/n’, ‘hotel’]
[‘Synonym’, ‘motel/_/hotel_building’, ‘hotel’]
[‘AtLocation’, ‘athelete’, ‘hotel’]
[‘AtLocation’, ‘eat_place’, ‘hotel’]
[‘AtLocation’, ‘entryway’, ‘hotel’]
[‘AtLocation’, ‘hide-a-bed_sofa’, ‘hotel’]
[‘AtLocation’, ‘hotel_room’, ‘hotel’]
[‘AtLocation’, ‘large_overprice_room’, ‘hotel’]
[‘AtLocation’, ‘phone_book’, ‘hotel’]
[‘AtLocation’, ‘reception’, ‘hotel’]
[‘AtLocation’, ‘school’, ‘hotel’]
[‘AtLocation’, ‘sex’, ‘hotel’]
[‘AtLocation’, ‘television’, ‘hotel’]
[‘RelatedTo’, ‘american_breakfast/n’, ‘hotel’]
[‘RelatedTo’, ‘bed’, ‘hotel’]
[‘RelatedTo’, ‘hall_porter/n’, ‘hotel’]
[‘RelatedTo’, ‘host/n’, ‘hotel’]
[‘RelatedTo’, ‘hostel/n’, ‘hotel’]
[‘RelatedTo’, ‘hostelry/n’, ‘hotel’]
[‘RelatedTo’, ‘hotel’, ‘inn’]
[‘RelatedTo’, ‘hotel’, ‘overnight’]
[‘RelatedTo’, ‘lady_lounge/n’, ‘hotel’]
[‘RelatedTo’, ‘motel’, ‘hotel’]
[‘RelatedTo’, ‘nonguest/n’, ‘hotel’]
[‘RelatedTo’, ‘room’, ‘hotel’]
[‘RelatedTo’, ‘visitor’, ‘hotel’]
[‘RelatedTo’, ‘wake-up_call/n’, ‘hotel’]
[‘Antonym’, ‘lodge’, ‘hotel’]
[‘AtLocation’, ‘bar_of_soap’, ‘hotel’]
[‘AtLocation’, ‘bed’, ‘hotel’]
[‘AtLocation’, ‘bidet’, ‘hotel’]
[‘AtLocation’, ‘coffee’, ‘hotel’]
[‘AtLocation’, ‘concierge’, ‘hotel’]
[‘AtLocation’, ‘disco’, ‘hotel’]
[‘AtLocation’, ‘guest’, ‘hotel’]
[‘AtLocation’, ‘hooker’, ‘hotel’]
[‘AtLocation’, ‘hospitality’, ‘hotel’]
[‘AtLocation’, ‘hotel’, ‘la_vega’]
[‘AtLocation’, ‘hotel’, ‘resort’]
[‘AtLocation’, ‘house’, ‘hotel’]
[‘AtLocation’, ‘litle_soap’, ‘hotel’]
[‘AtLocation’, ‘lodge’, ‘hotel’]
[‘AtLocation’, ‘luggage’, ‘hotel’]
[‘AtLocation’, ‘minibar’, ‘hotel’]
[‘AtLocation’, ‘porter’, ‘hotel’]
[‘AtLocation’, ‘reception_desk’, ‘hotel’]
[‘AtLocation’, ‘second_floor’, ‘hotel’]
[‘AtLocation’, ‘shower_curtain’, ‘hotel’]
[‘AtLocation’, ‘someone’, ‘hotel’]
[‘AtLocation’, ‘stair’, ‘hotel’]
[‘AtLocation’, ‘terrorist’, ‘hotel’]
[‘EtymologicallyDerivedFrom’, ‘hotel’, ‘hostel’]
[‘HasProperty’, ‘hotel’, ‘expensive’]
[‘RelatedTo’, ‘bell_captain/n’, ‘hotel’]
[‘RelatedTo’, ‘breakout/n’, ‘hotel’]
[‘RelatedTo’, ‘conference’, ‘hotel’]
[‘RelatedTo’, ‘first_class/a’, ‘hotel’]
[‘RelatedTo’, ‘hotel’, ‘commercial_house’]
[‘RelatedTo’, ‘hotel’, ‘eagle_song’]
[‘RelatedTo’, ‘hotel’, ‘guest’]
[‘RelatedTo’, ‘hotel’, ‘guest_room’]
[‘RelatedTo’, ‘hotel’, ‘sleep’]
[‘RelatedTo’, ‘hotel’, ‘song’]
[‘RelatedTo’, ‘hotel’, ‘stay_holiday’]
[‘RelatedTo’, ‘megahotel/n’, ‘hotel’]
[‘RelatedTo’, ‘multihotel/a’, ‘hotel’]
[‘RelatedTo’, ‘rack_rate/n’, ‘hotel’]
[‘RelatedTo’, ‘rate’, ‘hotel’]
[‘RelatedTo’, ‘reserve’, ‘hotel’]
[‘Synonym’, ‘commercial_lodge_organisation’, ‘hotel’]
[‘Synonym’, ‘hotel_build’, ‘hotel’]
[‘UsedFor’, ‘hotel’, ‘hold_meet’]
[‘UsedFor’, ‘hotel’, ‘place_to_camp_out_while_you_be_rest_from_travel’]
[‘UsedFor’, ‘hotel’, ‘place_to_sleep’]
[‘UsedFor’, ‘hotel’, ‘sleep_in’]
[‘AtLocation’, ‘accommodation’, ‘hotel’]
[‘AtLocation’, ‘balcony’, ‘hotel’]
[‘AtLocation’, ‘bar’, ‘hotel’]
[‘AtLocation’, ‘bathroom’, ‘hotel’]
[‘AtLocation’, ‘bed_sheet’, ‘hotel’]
[‘AtLocation’, ‘bible’, ‘hotel’]
[‘AtLocation’, ‘carpet’, ‘hotel’]
[‘AtLocation’, ‘cat’, ‘hotel’]
[‘AtLocation’, ‘computer’, ‘hotel’]
[‘AtLocation’, ‘front_room’, ‘hotel’]
[‘AtLocation’, ‘gift_shop’, ‘hotel’]
[‘AtLocation’, ‘good_food’, ‘hotel’]
[‘AtLocation’, ‘it’, ‘hotel’]
[‘AtLocation’, ‘little_soap’, ‘hotel’]
[‘AtLocation’, ‘passageway’, ‘hotel’]
[‘AtLocation’, ‘pee’, ‘hotel’]
[‘AtLocation’, ‘prostitute’, ‘hotel’]
[‘AtLocation’, ‘restaurant_dine_area’, ‘hotel’]
[‘AtLocation’, ‘sheet’, ‘hotel’]
[‘AtLocation’, ‘shower_stall’, ‘hotel’]
[‘AtLocation’, ‘telephone_room’, ‘hotel’]
[‘AtLocation’, ‘tire_person’, ‘hotel’]
[‘RelatedTo’, ‘bellhop/n’, ‘hotel’]
[‘RelatedTo’, ‘boatel/n’, ‘hotel’]
[‘RelatedTo’, ‘concierge/n’, ‘hotel’]
[‘RelatedTo’, ‘condo-hotel/n’, ‘hotel’]
[‘RelatedTo’, ‘full_board/n’, ‘hotel’]
[‘RelatedTo’, ‘guest/n’, ‘hotel’]
[‘RelatedTo’, ‘hotel’, ‘city’]
[‘RelatedTo’, ‘hotel’, ‘many_room’]
[‘RelatedTo’, ‘hotel’, ‘person_stay’]
[‘RelatedTo’, ‘hotelkeeping/n’, ‘hotel’]
[‘RelatedTo’, ‘miscellaneous_charge_order/n’, ‘hotel’]
[‘RelatedTo’, ‘property’, ‘hotel’]
[‘RelatedTo’, ‘regency’, ‘hotel’]
[‘RelatedTo’, ‘strip/n’, ‘hotel’]
[‘UsedFor’, ‘hotel’, ‘conference’]
[‘UsedFor’, ‘hotel’, ‘stay_overnight’]
[‘AtLocation’, ‘alcohol’, ‘hotel’]
[‘AtLocation’, ‘bake_pan’, ‘hotel’]
[‘AtLocation’, ‘bathroom_with_toilet’, ‘hotel’]
[‘AtLocation’, ‘beverage_service’, ‘hotel’]
[‘AtLocation’, ‘businessmen’, ‘hotel’]
[‘AtLocation’, ‘cotton_fiber’, ‘hotel’]
[‘AtLocation’, ‘hotel’, ‘any_city_with_airport’]
[‘AtLocation’, ‘hotel’, ‘city’]
[‘AtLocation’, ‘human’, ‘hotel’]
[‘AtLocation’, ‘kitchen’, ‘hotel’]
[‘AtLocation’, ‘luggage_carrier’, ‘hotel’]
[‘AtLocation’, ‘maid_service’, ‘hotel’]
[‘AtLocation’, ‘muscle’, ‘hotel’]
[‘AtLocation’, ‘outer_space’, ‘hotel’]
[‘AtLocation’, ‘plane’, ‘hotel’]
[‘AtLocation’, ‘separate_shower’, ‘hotel’]
[‘AtLocation’, ‘stapler’, ‘hotel’]
[‘AtLocation’, ‘suitcase’, ‘hotel’]
[‘AtLocation’, ‘suite’, ‘hotel’]
[‘AtLocation’, ‘telephone_book’, ‘hotel’]
[‘AtLocation’, ‘vacant_room’, ‘hotel’]
[‘HasA’, ‘hotel’, ‘check_in_desk’]
[‘HasA’, ‘hotel’, ‘front_desk’]
[‘HasA’, ‘hotel’, ‘lobby_on_first_floor’]
[‘RelatedTo’, ‘affair’, ‘hotel’]
[‘RelatedTo’, ‘apartotel/n’, ‘hotel’]
[‘RelatedTo’, ‘baby_listen/n’, ‘hotel’]
[‘RelatedTo’, ‘boot/n’, ‘hotel’]
[‘RelatedTo’, ‘botel/n’, ‘hotel’]
[‘RelatedTo’, ‘dormitory’, ‘hotel’]
[‘RelatedTo’, ‘fountain’, ‘hotel’]
[‘RelatedTo’, ‘hotel’, ‘accommodation’]
[‘RelatedTo’, ‘hotel’, ‘build’]
[‘RelatedTo’, ‘hotel’, ‘house’]
[‘RelatedTo’, ‘hotel’, ‘motel’]
[‘RelatedTo’, ‘hotel’, ‘place’]
[‘RelatedTo’, ‘inn’, ‘hotel’]
[‘RelatedTo’, ‘minibar/n’, ‘hotel’]
[‘RelatedTo’, ‘nonhotel/a’, ‘hotel’]
[‘RelatedTo’, ‘suite’, ‘hotel’]
[‘Synonym’, ‘commercial_lodge_organization’, ‘hotel’]
[‘Synonym’, ‘inn’, ‘hotel’]
[‘UsedFor’, ‘hotel’, ‘bed_away_from_home’]
[‘UsedFor’, ‘hotel’, ‘have_sex’]
[‘UsedFor’, ‘hotel’, ‘stay_away_from_home’]
[‘Antonym’, ‘camp’, ‘hotel’]
[‘AtLocation’, ‘bathroom_drawer’, ‘hotel’]
[‘AtLocation’, ‘bottle_wine’, ‘hotel’]
[‘AtLocation’, ‘buffet’, ‘hotel’]
[‘AtLocation’, ‘checkin_desk’, ‘hotel’]
[‘AtLocation’, ‘clean_lady’, ‘hotel’]
[‘AtLocation’, ‘clerk’, ‘hotel’]
[‘AtLocation’, ‘cocktail_cabinet’, ‘hotel’]
[‘AtLocation’, ‘desk_clerk’, ‘hotel’]
[‘AtLocation’, ‘front_desk’, ‘hotel’]
[‘AtLocation’, ‘hotel’, ‘a’]
[‘AtLocation’, ‘luggage_trolley’, ‘hotel’]
[‘AtLocation’, ‘miniature_soap_and_shampoo’, ‘hotel’]
[‘AtLocation’, ‘night_table’, ‘hotel’]
[‘AtLocation’, ‘passage’, ‘hotel’]
[‘AtLocation’, ‘pen’, ‘hotel’]
[‘AtLocation’, ‘place_to_stay’, ‘hotel’]
[‘AtLocation’, ‘reception_area’, ‘hotel’]
[‘AtLocation’, ‘restaurant’, ‘hotel’]
[‘AtLocation’, ‘restaurant_table’, ‘hotel’]
[‘AtLocation’, ‘serve_cart’, ‘hotel’]
[‘AtLocation’, ‘serve_trolley’, ‘hotel’]
[‘AtLocation’, ‘toilet’, ‘hotel’]
[‘HasA’, ‘hotel’, ‘lobby’]
[‘PartOf’, ‘lobby’, ‘hotel’]
[‘RelatedTo’, ‘bar’, ‘hotel’]
[‘RelatedTo’, ‘dock/n’, ‘hotel’]
[‘RelatedTo’, ‘double_room/n’, ‘hotel’]
[‘RelatedTo’, ‘fleabag/n’, ‘hotel’]
[‘RelatedTo’, ‘floatel/n’, ‘hotel’]
[‘RelatedTo’, ‘hotel’, ‘but_posh’]
[‘RelatedTo’, ‘hotel’, ‘concierge’]
[‘RelatedTo’, ‘hotel’, ‘maid’]
[‘RelatedTo’, ‘hotel’, ‘person’]
[‘RelatedTo’, ‘hotel’, ‘rent_room’]
[‘RelatedTo’, ‘hotel’, ‘residence’]
[‘RelatedTo’, ‘hotel’, ‘temporary_residence’]
[‘RelatedTo’, ‘hotel’, ‘there’]
[‘RelatedTo’, ‘hotelier/n’, ‘hotel’]
[‘RelatedTo’, ‘hotellike/a’, ‘hotel’]
[‘RelatedTo’, ‘kennel’, ‘hotel’]
[‘RelatedTo’, ‘minshuku/n’, ‘hotel’]
[‘RelatedTo’, ‘plaza’, ‘hotel’]
[‘RelatedTo’, ‘registration/n’, ‘hotel’]
[‘RelatedTo’, ‘room_service/n’, ‘hotel’]
[‘RelatedTo’, ‘ski_lodge/n’, ‘hotel’]
[‘RelatedTo’, ‘valet/n’, ‘hotel’]
[‘RelatedTo’, ‘where_can_i_find_hotel’, ‘hotel’]
[‘Synonym’, ‘inn/_/hotel_building’, ‘hotel’]
[‘EtymologicallyDerivedFrom’, ‘aparthotel’, ‘hotel’]
[‘EtymologicallyDerivedFrom’, ‘autohotel’, ‘hotel’]
[‘EtymologicallyDerivedFrom’, ‘hotelkeeping’, ‘hotel’]
[‘EtymologicallyDerivedFrom’, ‘boatel’, ‘hotel’]
[‘EtymologicallyDerivedFrom’, ‘condotel’, ‘hotel’]
[‘EtymologicallyDerivedFrom’, ‘hotellike’, ‘hotel’]
[‘EtymologicallyDerivedFrom’, ‘flotel’, ‘hotel’]
[‘EtymologicallyDerivedFrom’, ‘nonhotel’, ‘hotel’]
[‘CapableOf’, ‘hotel’, ‘spoil_look_of_holiday_destination’]
[‘EtymologicallyDerivedFrom’, ‘botel’, ‘hotel’]
[‘EtymologicallyDerivedFrom’, ‘love_hotel’, ‘hotel’]
[‘EtymologicallyDerivedFrom’, ‘floatel’, ‘hotel’]
[‘EtymologicallyDerivedFrom’, ‘horeca’, ‘hotel’]
[‘EtymologicallyDerivedFrom’, ‘motel’, ‘hotel’]
[‘CapableOf’, ‘hotel’, ‘book_room’]
[‘EtymologicallyDerivedFrom’, ‘hotelwide’, ‘hotel’]
[‘EtymologicallyDerivedFrom’, ‘megahotel’, ‘hotel’]

 

Plus a lot of examples of hotels:

[‘IsA’, ’21c_museum_hotel’, ‘hotel’]
[‘IsA’, ’42_call/n/hotel’, ‘hotel’]
[‘IsA’, ‘707_17th_street’, ‘hotel’]
[‘IsA’, ‘abbey_resort’, ‘hotel’]
[‘IsA’, ‘abraj_al_bait’, ‘hotel’]
[‘IsA’, ‘academy/n/hotel’, ‘hotel’]
[‘IsA’, ‘al_rasheed_hotel’, ‘hotel’]
[‘IsA’, ‘alaska_build’, ‘hotel’]
[‘IsA’, ‘amangalla’, ‘hotel’]
[‘IsA’, ‘aulani’, ‘hotel’]
[‘IsA’, ‘avari_tower’, ‘hotel’]
[‘IsA’, ‘beau-rivage_geneva’, ‘hotel’]
[‘IsA’, ‘belmont_house/n/montevideo’, ‘hotel’]
[‘IsA’, ‘berkeley’, ‘hotel’]
[‘IsA’, ‘britannia_adelphi_hotel’, ‘hotel’]
[‘IsA’, ‘camelback_inn’, ‘hotel’]
[‘IsA’, ‘canyon_hotel’, ‘hotel’]
[‘IsA’, ‘carlton_hotel/n/atascadero,_california’, ‘hotel’]
[‘IsA’, ‘casapueblo’, ‘hotel’]
[‘IsA’, ‘ch\\xc3\\xa2teau_laurier’, ‘hotel’]
[‘IsA’, ‘citygate_ecotower’, ‘hotel’]
[‘IsA’, ‘clift’, ‘hotel’]
[‘IsA’, ‘congress_hall/n/cape_may_hotel’, ‘hotel’]
[‘IsA’, ‘connaught/n/hotel’, ‘hotel’]
[‘IsA’, ‘copacabana_hotel_resid\\xc3\\xaancia’, ‘hotel’]
[‘IsA’, ‘corinthia_hotel_tripoli’, ‘hotel’]
[‘IsA’, ‘courtyard_by_marriott_pune’, ‘hotel’]
[‘IsA’, ‘covent_garden_hotel’, ‘hotel’]
[‘IsA’, ‘crowne_plaza_glasgow’, ‘hotel’]
[‘IsA’, ‘drake_hotel/n/toronto’, ‘hotel’]
[‘IsA’, ‘duke_of_edinburgh_hotel’, ‘hotel’]
[‘IsA’, ‘empire_landmark_hotel’, ‘hotel’]
[‘IsA’, ‘eventi’, ‘hotel’]
[‘IsA’, ‘excelsior_hotel_ernst’, ‘hotel’]
[‘IsA’, ‘fairmont_dubai’, ‘hotel’]
[‘IsA’, ‘fairmont_pacific_rim’, ‘hotel’]
[‘IsA’, ‘francisco_grande’, ‘hotel’]
[‘IsA’, ‘franklin_hotel_london’, ‘hotel’]
[‘IsA’, ‘fullerton_hotel_singapore’, ‘hotel’]
[‘IsA’, ‘gallery_hotel’, ‘hotel’]
[‘IsA’, ‘grand_imperial_hotel’, ‘hotel’]
[‘IsA’, ‘grand_lisboa’, ‘hotel’]
[‘IsA’, ‘grand_oasis_palace_de_muro’, ‘hotel’]
[‘IsA’, ‘grange_holborn_hotel’, ‘hotel’]
[‘IsA’, ‘grosvenor_house_hotel’, ‘hotel’]
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[‘IsA’, ‘westin_charlotte’, ‘hotel’]
[‘IsA’, ‘westin_providence’, ‘hotel’]
[‘IsA’, ‘abbasi_hotel’, ‘hotel’]
[‘IsA’, ‘absheron_hotel’, ‘hotel’]
[‘IsA’, ‘amanjiwo’, ‘hotel’]
[‘IsA’, ‘avalon_hotel/n/gothenburg’, ‘hotel’]
[‘IsA’, ‘bacara_resort’, ‘hotel’]
[‘IsA’, ‘baiyoke_tower_ii’, ‘hotel’]
[‘IsA’, ‘baron_hotel’, ‘hotel’]
[‘IsA’, ‘bear_hotel/n/oxfordshire’, ‘hotel’]
[‘IsA’, ‘bentley_london’, ‘hotel’]
[‘IsA’, ‘burj_al_arab’, ‘hotel’]
[‘IsA’, ‘carter_house_inn’, ‘hotel’]
[‘IsA’, ‘chateau_lake_louise’, ‘hotel’]
[‘IsA’, ‘claremont_resort’, ‘hotel’]
[‘IsA’, ‘club_quarter_hotel/n/houston’, ‘hotel’]
[‘IsA’, ‘copenhagen_admiral_hotel’, ‘hotel’]
[‘IsA’, ‘corinthia_hotel_khartoum’, ‘hotel’]
[‘IsA’, ‘detroit_statler_hotel’, ‘hotel’]
[‘IsA’, ‘dom-hotel’, ‘hotel’]
[‘IsA’, ‘dorchester’, ‘hotel’]
[‘IsA’, ‘dorint_hotel_tower’, ‘hotel’]
[‘IsA’, ‘dryburgh_abbey_hotel’, ‘hotel’]
[‘IsA’, ‘egerton_grey_country_house_hotel’, ‘hotel’]
[‘IsA’, ‘fairmont_royal_pavilion/n/resort’, ‘hotel’]
[‘IsA’, ‘fisherman_cove’, ‘hotel’]
[‘IsA’, ‘flitwick_manor’, ‘hotel’]
[‘IsA’, ‘four_season_hotel_hong_kong’, ‘hotel’]
[‘IsA’, ‘four_season_london’, ‘hotel’]
[‘IsA’, ‘garden_hotel_guangzhou’, ‘hotel’]
[‘IsA’, ‘gaylord_national_resort_convention_center’, ‘hotel’]
[‘IsA’, ‘gran_hotel/n/palma’, ‘hotel’]
[‘IsA’, ‘grand_hotel/n/oslo’, ‘hotel’]
[‘IsA’, ‘grand_hotel/n/taipei’, ‘hotel’]
[‘IsA’, ‘grand_hotel_tripoli’, ‘hotel’]
[‘IsA’, ‘grand_hyatt_new_york’, ‘hotel’]
[‘IsA’, ‘grande_bretagne’, ‘hotel’]
[‘IsA’, ‘green_tree_inn’, ‘hotel’]
[‘IsA’, ‘heetal_plaza_hotel’, ‘hotel’]
[‘IsA’, ‘herod_hotel’, ‘hotel’]
[‘IsA’, ‘hilton_glasgow_hotel’, ‘hotel’]
[‘IsA’, ‘hotel’, ‘artifact_type_by_function’]
[‘IsA’, ‘hotel’, ‘nice_place_to_spend_vacation’]
[‘IsA’, ‘hotel’, ‘place_where_you_sleep’]
[‘IsA’, ‘hotel_de_l_europe/n/amsterdam’, ‘hotel’]
[‘IsA’, ‘hotel_druk’, ‘hotel’]
[‘IsA’, ‘hotel_gl\\xc3\\xb3ria’, ‘hotel’]
[‘IsA’, ‘hotel_imperial’, ‘hotel’]
[‘IsA’, ‘hotel_kangerlussuaq’, ‘hotel’]
[‘IsA’, ‘hotel_landmark_canton’, ‘hotel’]
[‘IsA’, ‘hotel_macdonald’, ‘hotel’]
[‘IsA’, ‘hotel_mehran’, ‘hotel’]
[‘IsA’, ‘hotel_newfoundland’, ‘hotel’]
[‘IsA’, ‘hotel_vatel_and_spa’, ‘hotel’]
[‘IsA’, ‘hyatt_regency_albuquerque’, ‘hotel’]
[‘IsA’, ‘hyatt_regency_houston’, ‘hotel’]
[‘IsA’, ‘hyatt_regency_san_francisco’, ‘hotel’]
[‘IsA’, ‘hydro_majestic_hotel’, ‘hotel’]
[‘IsA’, ‘h\\xc3\\xb4tel_le_bristol_paris’, ‘hotel’]
[‘IsA’, ‘h\\xc3\\xb4tel_montana’, ‘hotel’]
[‘IsA’, ‘inter_continental_manila’, ‘hotel’]
[‘IsA’, ‘inter_continental_muscat’, ‘hotel’]
[‘IsA’, ‘international_dateline_hotel’, ‘hotel’]
[‘IsA’, ‘jin_mao_tower’, ‘hotel’]
[‘IsA’, ‘jumeirah_essex_house’, ‘hotel’]
[‘IsA’, ‘jw_marriott_bogot\\xc3\\xa1′, ‘hotel’]
[‘IsA’, ‘jw_marriott_shanghai’, ‘hotel’]
[‘IsA’, ‘kempinski_hotel_ajman’, ‘hotel’]
[‘IsA’, ‘langham_place_hotel’, ‘hotel’]
[‘IsA’, ‘le_meridien_mariador_palace’, ‘hotel’]
[‘IsA’, ‘le_m\\xc3\\xa9ridien_san_francisco’, ‘hotel’]
[‘IsA’, ‘mandarin_oriental_paris’, ‘hotel’]
[‘IsA’, ‘mandarin_oriental_singapore’, ‘hotel’]
[‘IsA’, ‘mansion_on_o_street’, ‘hotel’]
[‘IsA’, ‘marbella_club_hotel’, ‘hotel’]
[‘IsA’, ‘marriott_grande_vista’, ‘hotel’]
[‘IsA’, ‘marriott_west_india_quay’, ‘hotel’]
[‘IsA’, ‘mauna_kea_beach_hotel’, ‘hotel’]
[‘IsA’, ‘meet_hotel_leeds’, ‘hotel’]
[‘IsA’, ‘milford_plaza_hotel’, ‘hotel’]
[‘IsA’, ‘millennium_madejski_hotel’, ‘hotel’]
[‘IsA’, ‘millennium_tower/n/las_vegas’, ‘hotel’]
[‘IsA’, ‘moresby_hall’, ‘hotel’]
[‘IsA’, ‘muna_hotel’, ‘hotel’]
[‘IsA’, ‘m\\xc3\\xb6venpick_hotel_ramallah’, ‘hotel’]
[‘IsA’, ‘nansloe_manor’, ‘hotel’]
[‘IsA’, ‘nara_hotel’, ‘hotel’]
[‘IsA’, ‘new_yorker_hotel’, ‘hotel’]
[‘IsA’, ‘northeast_asia_trade_tower’, ‘hotel’]
[‘IsA’, ‘oberoi_hotel_resort’, ‘hotel’]
[‘IsA’, ‘old_bank_hotel_oxford’, ‘hotel’]
[‘IsA’, ‘oriental_hotel/n/kobe,_japan’, ‘hotel’]
[‘IsA’, ‘penally_abbey’, ‘hotel’]
[‘IsA’, ‘peninsula_chicago’, ‘hotel’]
[‘IsA’, ‘pennyhill_park_hotel’, ‘hotel’]
[‘IsA’, ‘radisson_royal_hotel_moscow’, ‘hotel’]
[‘IsA’, ‘raffle_hotel’, ‘hotel’]
[‘IsA’, ‘renaissance_kota_bharu_hotel’, ‘hotel’]
[‘IsA’, ‘ritz_hotel’, ‘hotel’]
[‘IsA’, ‘rogner_hotel’, ‘hotel’]
[‘IsA’, ‘rosa_grand’, ‘hotel’]
[‘IsA’, ‘rose_tower’, ‘hotel’]
[‘IsA’, ‘royalton_hotel’, ‘hotel’]
[‘IsA’, ‘selsdon_park_hotel’, ‘hotel’]
[‘IsA’, ‘settha_palace_hotel’, ‘hotel’]
[‘IsA’, ‘sheraton_club_de_pin_resort’, ‘hotel’]
[‘IsA’, ‘something_you_find_downtown’, ‘hotel’]
[‘IsA’, ‘swiss\\xc3\\xb4tel_krasnye_holmy_moscow’, ‘hotel’]
[‘IsA’, ‘tibesti_hotel’, ‘hotel’]
[‘IsA’, ‘tower_verre’, ‘hotel’]
[‘IsA’, ‘villa_marina_hotel’, ‘hotel’]
[‘IsA’, ‘w_san_francisco’, ‘hotel’]
[‘IsA’, ‘westin_bonaventure_hotel’, ‘hotel’]
[‘IsA’, ‘westin_peachtree_plaza_hotel’, ‘hotel’]
[‘IsA’, ‘westin_san_francisco_market_street’, ‘hotel’]
[‘IsA’, ‘windamere_hotel’, ‘hotel’]
[‘IsA’, ‘winecoff_hotel’, ‘hotel’]
[‘IsA’, ‘1717_broadway’, ‘hotel’]
[‘IsA’, ‘al_deira_hotel’, ‘hotel’]
[‘IsA’, ‘artisan_hotel’, ‘hotel’]
[‘IsA’, ‘atlantis_palm’, ‘hotel’]
[‘IsA’, ‘austria_classic_hotel_wien’, ‘hotel’]
[‘IsA’, ‘baltimore_marriott_waterfront_hotel’, ‘hotel’]
[‘IsA’, ‘bedford_hotel/n/brighton’, ‘hotel’]
[‘IsA’, ‘bell_tower_hotel’, ‘hotel’]
[‘IsA’, ‘beverly_hill_hotel’, ‘hotel’]
[‘IsA’, ‘bintan_agro_beach_resort’, ‘hotel’]
[‘IsA’, ‘blake_hotel’, ‘hotel’]
[‘IsA’, ‘boca_raton_resort’, ‘hotel’]
[‘IsA’, ‘bogot\\xc3\\xa1_marriott_hotel’, ‘hotel’]
[‘IsA’, ‘buckingham_hotel’, ‘hotel’]
[‘IsA’, ‘burj_al_alam’, ‘hotel’]
[‘IsA’, ‘cally_palace’, ‘hotel’]
[‘IsA’, ‘capital_hotel’, ‘hotel’]
[‘IsA’, ‘carbis_bay_hotel’, ‘hotel’]
[‘IsA’, ‘celtic_manor_resort’, ‘hotel’]
[‘IsA’, ‘charlotte_street_hotel’, ‘hotel’]
[‘IsA’, ‘conrad_centennial_singapore’, ‘hotel’]
[‘IsA’, ‘damenlou_hotel’, ‘hotel’]
[‘IsA’, ‘digby_pine_resort’, ‘hotel’]
[‘IsA’, ‘dog_bark_park_inn’, ‘hotel’]
[‘IsA’, ‘don_ce_sar’, ‘hotel’]
[‘IsA’, ‘donegana_hotel_montreal’, ‘hotel’]
[‘IsA’, ‘dragon_hill_lodge’, ‘hotel’]
[‘IsA’, ‘dubai_tower_doha’, ‘hotel’]
[‘IsA’, ‘dunstane_house’, ‘hotel’]
[‘IsA’, ‘empress_hotel/n/new_jersey’, ‘hotel’]
[‘IsA’, ‘fairmont_acapulco_princess’, ‘hotel’]
[‘IsA’, ‘fairmont_beijing’, ‘hotel’]
[‘IsA’, ‘fairmont_palliser_hotel’, ‘hotel’]
[‘IsA’, ‘federal_kuala_lumpur’, ‘hotel’]
[‘IsA’, ‘forbury_hotel’, ‘hotel’]
[‘IsA’, ‘full_moon_hotel’, ‘hotel’]
[‘IsA’, ‘glenapp_castle’, ‘hotel’]
[‘IsA’, ‘grand_hotel_sofia’, ‘hotel’]
[‘IsA’, ‘grange_city_hotel’, ‘hotel’]
[‘IsA’, ‘harbo_rcenter’, ‘hotel’]
[‘IsA’, ‘harvey_cedar_hotel’, ‘hotel’]
[‘IsA’, ‘hay\\xe2\\x80\\x93_adam_hotel’, ‘hotel’]
[‘IsA’, ‘hedonism_resort’, ‘hotel’]
[‘IsA’, ‘hilton_san_francisco_financial_district’, ‘hotel’]
[‘IsA’, ‘hilton_washington’, ‘hotel’]
[‘IsA’, ‘hockley_highland_inn’, ‘hotel’]
[‘IsA’, ‘hot_pads.com’, ‘hotel’]
[‘IsA’, ‘hotel_africana’, ‘hotel’]
[‘IsA’, ‘hotel_ambo_mundos/n/havana’, ‘hotel’]
[‘IsA’, ‘hotel_charlottetown’, ‘hotel’]
[‘IsA’, ‘hotel_continental_oslo’, ‘hotel’]
[‘IsA’, ‘hotel_d_angleterre’, ‘hotel’]
[‘IsA’, ‘hotel_equatoria’, ‘hotel’]
[‘IsA’, ‘hotel_grand_chancellor_launceston’, ‘hotel’]
[‘IsA’, ‘hotel_kenney’, ‘hotel’]
[‘IsA’, ‘hotel_organization’, ‘hotel’]
[‘IsA’, ‘hotel_royal_christiania’, ‘hotel’]
[‘IsA’, ‘hotel_sisimiut’, ‘hotel’]
[‘IsA’, ‘hotel_ureka’, ‘hotel’]
[‘IsA’, ‘imperial_royale_hotel’, ‘hotel’]
[‘IsA’, ‘inn_at_perry_cabin’, ‘hotel’]
[‘IsA’, ‘inter_continental_toronto_centre’, ‘hotel’]
[‘IsA’, ‘island_shangri-la_hong_kong’, ‘hotel’]
[‘IsA’, ‘jamaica_pegasus_hotel’, ‘hotel’]
[‘IsA’, ‘jumeirah_emirate_tower_hotel’, ‘hotel’]
[‘IsA’, ‘jupiter_hotel’, ‘hotel’]
[‘IsA’, ‘keio_plaza_hotel’, ‘hotel’]
[‘IsA’, ‘landmark_london’, ‘hotel’]
[‘IsA’, ‘langham_place_new_york’, ‘hotel’]
[‘IsA’, ‘lao_plaza_hotel’, ‘hotel’]
[‘IsA’, ‘le_pavillon_hotel’, ‘hotel’]
[‘IsA’, ‘london_hilton_on_park_lane’, ‘hotel’]
[‘IsA’, ‘loola_adventure_resort’, ‘hotel’]
[‘IsA’, ‘maesmawr_hall’, ‘hotel’]
[‘IsA’, ‘manchester_grand_hyatt_hotel’, ‘hotel’]
[‘IsA’, ‘mandarin_oriental_bangkok’, ‘hotel’]
[‘IsA’, ‘mandarin_oriental_hyde_park_london’, ‘hotel’]
[‘IsA’, ‘mardan_palace’, ‘hotel’]
[‘IsA’, ‘may_fair’, ‘hotel’]
[‘IsA’, ‘milad_tower’, ‘hotel’]
[‘IsA’, ‘millennium_biltmore_hotel’, ‘hotel’]
[‘IsA’, ‘new_york_marriott_marquis’, ‘hotel’]
[‘IsA’, ‘nh_grand_hotel_krasnapolsky’, ‘hotel’]
[‘IsA’, ‘nickelodeon_suite_resort’, ‘hotel’]
[‘IsA’, ‘oberoi_trident’, ‘hotel’]
[‘IsA’, ‘palazzo_versace_australia’, ‘hotel’]
[‘IsA’, ‘peebles_hydro’, ‘hotel’]
[‘IsA’, ‘peninsula_tokyo’, ‘hotel’]
[‘IsA’, ‘pu_li_hotel_and_spa’, ‘hotel’]
[‘IsA’, ‘renaissance_dallas_hotel’, ‘hotel’]
[‘IsA’, ‘royal_victoria_hotel’, ‘hotel’]
[‘IsA’, ‘sheikhpura_kothi’, ‘hotel’]
[‘IsA’, ‘sheraton_ankara’, ‘hotel’]
[‘IsA’, ‘sheraton_hotel_and_resort’, ‘hotel’]
[‘IsA’, ‘sheraton_park_tower_hotel’, ‘hotel’]
[‘IsA’, ‘sheraton_tirana_hotel_and_tower’, ‘hotel’]
[‘IsA’, ‘sofitel_macau_at_ponte_16′, ‘hotel’]
[‘IsA’, ‘temple_garden_mineral_spa_resort’, ‘hotel’]
[‘IsA’, ‘three_crown_hotel’, ‘hotel’]
[‘IsA’, ‘tipton_hotel’, ‘hotel’]
[‘IsA’, ‘westin_palace_milan’, ‘hotel’]
[‘IsA’, ‘westin_paris’, ‘hotel’]
[‘IsA’, ‘westin_westminster’, ‘hotel’]
[‘IsA’, ‘wrest_point_hotel_casino’, ‘hotel’]
[‘IsA’, ’22_jermyn_street’, ‘hotel’]
[‘IsA’, ‘995_fifth_avenue’, ‘hotel’]
[‘IsA’, ‘ambasador_hotel’, ‘hotel’]
[‘IsA’, ‘ambassador-monaco’, ‘hotel’]
[‘IsA’, ‘american_hotel_amsterdam’, ‘hotel’]
[‘IsA’, ‘andaz_west_hollywood’, ‘hotel’]
[‘IsA’, ‘astoria_palace_hotel’, ‘hotel’]
[‘IsA’, ‘bab_el_bahr_hotel’, ‘hotel’]
[‘IsA’, ‘badrutt_palace_hotel’, ‘hotel’]
[‘IsA’, ‘banyan_tree_bintan’, ‘hotel’]
[‘IsA’, ‘basin_harbor_club’, ‘hotel’]
[‘IsA’, ‘boston_harbor_hotel’, ‘hotel’]
[‘IsA’, ‘carimar_beach_club’, ‘hotel’]
[‘IsA’, ‘cavendish_hotel’, ‘hotel’]
[‘IsA’, ‘central_hotel/n/glasgow’, ‘hotel’]
[‘IsA’, ‘chase_park_plaza’, ‘hotel’]
[‘IsA’, ‘chedi_muscat’, ‘hotel’]
[‘IsA’, ‘churchill_hotel’, ‘hotel’]
[‘IsA’, ‘clarion_hotel_limerick’, ‘hotel’]
[‘IsA’, ‘copthorne_hotel_cardiff’, ‘hotel’]
[‘IsA’, ‘courthouse_hotel’, ‘hotel’]
[‘IsA’, ‘courtyard_by_marriott_hyderabad’, ‘hotel’]
[‘IsA’, ‘crowne_plaza_liverpool_john_lennon_airport_hotel’, ‘hotel’]
[‘IsA’, ‘dariush_grand_hotel’, ‘hotel’]
[‘IsA’, ‘devigarh’, ‘hotel’]
[‘IsA’, ‘don_chan_palace’, ‘hotel’]
[‘IsA’, ‘dronninglund_hotel’, ‘hotel’]
[‘IsA’, ‘el-djazair’, ‘hotel’]
[‘IsA’, ‘farhat_hotel’, ‘hotel’]
[‘IsA’, ‘fort_garry_hotel’, ‘hotel’]
[‘IsA’, ‘four_point_by_sheraton_niagara_fall’, ‘hotel’]
[‘IsA’, ‘four_season_resort_hualalai’, ‘hotel’]
[‘IsA’, ‘fujiya_hotel’, ‘hotel’]
[‘IsA’, ‘gaylord_opryland_resort_convention_center’, ‘hotel’]
[‘IsA’, ‘george_hotel_crawley’, ‘hotel’]
[‘IsA’, ‘golden_cloud’, ‘hotel’]
[‘IsA’, ‘grand_hotel_benghazi’, ‘hotel’]
[‘IsA’, ‘grand_hotel_birmingham’, ‘hotel’]
[‘IsA’, ‘grand_hyatt_cairo’, ‘hotel’]
[‘IsA’, ‘grand_hyatt_hong_kong’, ‘hotel’]
[‘IsA’, ‘grandhotel_pupp’, ‘hotel’]
[‘IsA’, ‘hilton_walt_disney_world’, ‘hotel’]
[‘IsA’, ‘holt_hotel/n/oxfordshire’, ‘hotel’]
[‘IsA’, ‘hotel’, ‘big_than_breadbox’]
[‘IsA’, ‘hotel’, ‘build’]
[‘IsA’, ‘hotel’, ‘place_to_stop_by’]
[‘IsA’, ‘hotel_bahia/n/malabo’, ‘hotel’]
[‘IsA’, ‘hotel_bel-air’, ‘hotel’]
[‘IsA’, ‘hotel_carter_manhattan’, ‘hotel’]
[‘IsA’, ‘hotel_de_art’, ‘hotel’]
[‘IsA’, ‘hotel_de_paris’, ‘hotel’]
[‘IsA’, ‘hotel_el-aurassi’, ‘hotel’]
[‘IsA’, ‘hotel_grand_chancellor’, ‘hotel’]
[‘IsA’, ‘hotel_habana_riviera’, ‘hotel’]
[‘IsA’, ‘hotel_inglaterra’, ‘hotel’]
[‘IsA’, ‘hotel_jumolhari’, ‘hotel’]
[‘IsA’, ‘hotel_nacional_de_cuba’, ‘hotel’]
[‘IsA’, ‘hotel_panafrica’, ‘hotel’]
[‘IsA’, ‘hotel_pyr\\xc3\\xa9n\\xc3\\xa9es’, ‘hotel’]
[‘IsA’, ‘hotel_sacher’, ‘hotel’]
[‘IsA’, ‘hotel_tobruk’, ‘hotel’]
[‘IsA’, ‘hotel_zianides’, ‘hotel’]
[‘IsA’, ‘h\\xc3\\xb4tel_de_crillon’, ‘hotel’]
[‘IsA’, ‘h\\xc3\\xb4tel_george-v’, ‘hotel’]
[‘IsA’, ‘ice_hotel/n/quebec’, ‘hotel’]
[‘IsA’, ‘ilikai’, ‘hotel’]
[‘IsA’, ‘imperial_botanical_beach_hotel’, ‘hotel’]
[‘IsA’, ‘imperial_new_delhi’, ‘hotel’]
[‘IsA’, ‘inter_continental_london’, ‘hotel’]
[‘IsA’, ‘inter_continental_san_francisco’, ‘hotel’]
[‘IsA’, ‘ishtar_sheraton_hotel’, ‘hotel’]
[‘IsA’, ‘jefferson_hotel/n/richmond,_virginia’, ‘hotel’]
[‘IsA’, ‘jumeirah_beach_hotel’, ‘hotel’]
[‘IsA’, ‘jw_marriott_mumbai’, ‘hotel’]
[‘IsA’, ‘jw_marriott_san_francisco_union_square’, ‘hotel’]
[‘IsA’, ‘kampala_intercontinental_hotel’, ‘hotel’]
[‘IsA’, ‘la_li_t_hotel_palace_and_resort’, ‘hotel’]
[‘IsA’, ‘lainston_house’, ‘hotel’]
[‘IsA’, ‘langham_hotel_london’, ‘hotel’]
[‘IsA’, ‘le_v’, ‘hotel’]
[‘IsA’, ‘limketkai_hotel_and_resort’, ‘hotel’]
[‘IsA’, ‘lloyd_hotel’, ‘hotel’]
[‘IsA’, ‘loews_vanderbilt_hotel’, ‘hotel’]
[‘IsA’, ‘lovat_hotel’, ‘hotel’]
[‘IsA’, ‘maple_leaf_square’, ‘hotel’]
[‘IsA’, ‘marriott_at_key_center’, ‘hotel’]
[‘IsA’, ‘marshall_hotel’, ‘hotel’]
[‘IsA’, ‘masindi_hotel’, ‘hotel’]
[‘IsA’, ‘midtown_grand’, ‘hotel’]
[‘IsA’, ‘miri_marriott_resort_spa’, ‘hotel’]
[‘IsA’, ‘miskin_manor’, ‘hotel’]
[‘IsA’, ‘north_west_castle’, ‘hotel’]
[‘IsA’, ‘ocean_house_rhode_island’, ‘hotel’]
[‘IsA’, ‘one_aldwych’, ‘hotel’]
[‘IsA’, ‘one_devonshire_garden’, ‘hotel’]
[‘IsA’, ‘one_wall_centre’, ‘hotel’]
[‘IsA’, ‘paramount_hotel’, ‘hotel’]
[‘IsA’, ‘peninsula_bangkok’, ‘hotel’]
[‘IsA’, ‘peninsula_new_york’, ‘hotel’]
[‘IsA’, ‘rio_othon_palace’, ‘hotel’]
[‘IsA’, ‘royal_cliff_hotel_group’, ‘hotel’]
[‘IsA’, ‘royal_hawaiian_hotel’, ‘hotel’]
[‘IsA’, ‘royal_horseguards_hotel’, ‘hotel’]
[‘IsA’, ‘rufflets_hotel’, ‘hotel’]
[‘IsA’, ‘shanker_hotel’, ‘hotel’]
[‘IsA’, ‘sheraton_aleppo_hotel’, ‘hotel’]
[‘IsA’, ‘sheraton_d\\xc3\\xbcsseldorf_airport_hotel’, ‘hotel’]
[‘IsA’, ‘sheraton_waikiki_hotel’, ‘hotel’]
[‘IsA’, ‘sorrento_hotel’, ‘hotel’]
[‘IsA’, ‘south_lodge_hotel’, ‘hotel’]
[‘IsA’, ‘stanford_court_hotel’, ‘hotel’]
[‘IsA’, ‘thistle_atlantic_tower’, ‘hotel’]
[‘IsA’, ‘townhouse_designhotel_maastricht’, ‘hotel’]
[‘IsA’, ‘us_flagship_hotel’, ‘hotel’]
[‘IsA’, ‘vdara’, ‘hotel’]
[‘IsA’, ‘west_athens_tower’, ‘hotel’]
[‘IsA’, ‘westin_st._francis’, ‘hotel’]
[‘IsA’, ‘william_penn_hotel’, ‘hotel’]
[‘IsA’, ‘wyndham_grand_chelsea_harbour’, ‘hotel’]

MIT ConceptNet5

I ran into Henry Lieberman (MIT) at AAAI15 conference on Artificial Intelligence/Robotics/CognitiveScience (AI/Robotics/CogSci).

Henry suggested that I check out MIT’s ConceptNet5 (http://conceptnet5.media.mit.edu/), which can be thought of as a large collection of facts.   The facts have been collected from many sources, some more reliable than others, so rather than call them facts, we should really call them assertions that people have made about the world.   A lot of the assertions are simple commonsense  – for example, “an apple is a fruit.”   However, to make all these assertions useful to artificial intelligence programmers and others, the assertions have been encoded in ConceptNet5 in a special computer readable format; and so one would write something like [/r/IsA, /c/en/apple, /c/en/fruit], where /r/ says what comes next is a relation, and /c/en/ says what comes next is an English concept.

So ConceptNet5 contains over 10 million assertions, and about 7 million of those assertions are in English.   There are 50 relations, and 2,798,486 English concepts.  As a graph, just the English part is about 3 million nodes and 7 millon edges or arcs connecting them.   That is a pretty big graph or network.

Anyone who wants the latest version of ConceptNet5 can download it from here: http://conceptnet5.media.mit.edu/downloads/v5.3/

I downloaded the CSV version, and wrote a simple Python program to help me peer inside.

Here is what I found:

Here are the 50 relations that I found, and how frequently they are used to connect to English concepts:
[[‘IsA’, 4762459], [‘RelatedTo’, 1114866], [‘PartOf’, 613269], [‘AtLocation’, 321706], [‘EtymologicallyDerivedFrom’, 192612], [‘DerivedFrom’, 93861], [‘Synonym’, 84240], [‘UsedFor’, 40596], [‘CapableOf’, 33082], [‘HasSubevent’, 23730], [‘Antonym’, 23173], [‘HasPrerequisite’, 21821], [‘HasProperty’, 17446], [‘Causes’, 16279], [‘MotivatedByGoal’, 14079], [‘MemberOf’, 10770], [‘SimilarTo’, 10121], [‘ReceivesAction’, 9354], [‘HasA’, 8615], [‘HasContext’, 7862], [‘InstanceOf’, 7584], [‘DefinedAs’, 5641], [‘CausesDesire’, 4515], [‘Desires’, 4471], [‘NotDesires’, 3755], [‘HasFirstSubevent’, 3727], [‘wordnet/adjectivePertainsTo’, 3309], [‘TranslationOf’, 2781], [‘HasLastSubevent’, 2690], [‘NotCapableOf’, 2542], [‘wordnet/adverbPertainsTo’, 2520], [‘MadeOf’, 1906], [‘NotHasProperty’, 1003], [‘Attribute’, 560], [‘CreatedBy’, 444], [‘NotIsA’, 420], [‘NotHasA’, 366], [‘Entails’, 356], [‘DesireOf’, 237], [‘InheritsFrom’, 156], [‘SymbolOf’, 144], [‘LocatedNear’, 83], [‘wordnet/participleOf’, 53], [‘LocationOfAction’, 40], [‘NotMadeOf’, 21], [‘SimilarSize’, 8], [‘CompoundDerivedFrom’, 2], [‘NotCauses’, 1], [‘HasPainIntensity’, 1], [‘HasPainCharacter’, 1]]

Here are the top 400 English concepts I found:
[[‘place’, 458623], [‘person’, 372535], [‘populate_place’, 314554], [‘settlement’, 282695], [‘specie’, 160865], [‘eukaryote’, 157531], [‘organisation’, 147159], [‘athlete’, 135201], [‘animal’, 115268], [‘musical_work’, 92150], [‘architectural_structure’, 91854], [‘album’, 90849], [‘village’, 82999], [‘soccer_player’, 58769], [‘build’, 56700], [‘artist’, 53704], [‘film’, 52730], [‘infrastructure’, 46068], [‘insect’, 44132], [‘plant’, 39688], [‘natural_place’, 39221], [‘company’, 35486], [‘town’, 33524], [‘educational_institution’, 32907], [‘single’, 31946], [‘mean_of_transportation’, 31604], [‘write_work’, 30422], [‘administrative_region’, 27698], [‘musical_artist’, 27183], [‘body_of_water’, 26173], [‘office_holder’, 23408], [‘band’, 22847], [‘school’, 22698], [‘software’, 22422], [‘book’, 22403], [‘mollusca’, 21282], [‘broadcaster’, 21169], [‘ship’, 20790], [‘politician’, 20651], [‘event’, 20319], [‘route_of_transportation’, 20076], [‘river’, 19185], [‘stream’, 18402], [‘television_show’, 17129], [‘military_person’, 17021], [‘populate_area’, 15714], [‘station’, 15424], [‘business’, 15284], [‘unite_state’, 15121], [‘video_game’, 14993], [‘radio_station’, 14910], [‘road’, 14699], [‘city’, 13956], [‘baseball_player’, 13709], [‘fish’, 13337], [‘unincorporated_area’, 13231], [‘sport_team’, 12992], [‘actor’, 12893], [‘soccer_club’, 12705], [‘university’, 12412], [‘bird’, 12239], [‘gridiron_football_player’, 11465], [‘planet’, 11404], [‘mountain’, 11187], [‘writer’, 10916], [‘protein’, 10795], [‘military_unit’, 10352], [‘site’, 10312], [‘scientist’, 10246], [‘device’, 10230], [‘airport’, 9858], [‘organization’, 9776], [‘club’, 9386], [‘movie’, 9302], [‘musical_composition’, 9278], [‘periodical_literature’, 9274], [‘flower_plant’, 9222], [‘live_thing’, 9018], [‘fowl’, 8859], [‘greenery’, 8851], [‘township’, 8831], [‘computer_game’, 8821], [‘educational_organization’, 8820], [‘watercourse’, 8818], [‘military_personnel’, 8806], [‘tv_show’, 8754], [‘musical_performer’, 8746], [‘underspecified_location’, 8734], [‘software_object’, 8730], [‘music_single’, 8726], [‘soccer_manager’, 8689], [‘ice_hockey_player’, 8686], [‘self-powered_vehicle’, 8671], [‘single-broadcast_tv_show’, 8464], [‘lake’, 8436], [‘military_conflict’, 8389], [‘mammal’, 8318], [‘troop’, 8224], [‘car_engine’, 8174], [‘street’, 8168], [‘football_player’, 7790], [‘facility’, 7768], [‘mollusk’, 7663], [‘masovian_voivodeship’, 7563], [‘privately_hold_company’, 7548], [‘cricketer’, 7546], [‘fungus’, 7462], [‘soccer_coach’, 7407], [‘fictitious_character’, 7265], [‘conflict’, 7255], [‘fictional_character’, 7055], [‘rugby_player’, 6897], [‘state_school’, 6772], [‘drug’, 6758], [‘car’, 6753], [‘chemical_compound’, 6744], [‘chemical_substance’, 6398], [‘amphibian’, 6277], [‘aircraft’, 6273], [‘census-designated_place’, 6263], [‘american_football_player’, 6245], [‘television_episode’, 6244], [‘reptile’, 6149], [‘california’, 6131], [‘stadium’, 6050], [‘disease’, 5777], [‘television_station’, 5679], [‘cleric’, 5623], [‘language’, 5461], [‘non-‘, 5339], [‘-ly’, 5310], [‘british_royalty’, 5143], [‘protect_area’, 5045], [‘great_poland_voivodeship’, 5036], [‘model_airplane’, 4961], [‘public_company’, 4789], [‘clergyman’, 4783], [‘historic_place’, 4730], [‘newspaper’, 4658], [‘song’, 4592], [‘un-‘, 4569], [‘sport_event’, 4567], [‘cartoon_character’, 4457], [‘weapon’, 4415], [‘member_of_parliament’, 4306], [‘illness’, 4289], [‘comic_character’, 4285], [‘college_coach’, 4250], [‘geographical_region’, 4250], [‘\\xc5\\x82\\xc3\\xb3d\\xc5\\xba_voivodeship’, 4187], [‘township/n/united_states’, 4087], [‘private_school’, 3858], [‘-ness’, 3843], [‘automobile’, 3843], [‘new_york’, 3841], [‘khuzestan_province’, 3787], [‘basketball_player’, 3746], [‘country’, 3725], [‘lublin_voivodeship’, 3706], [‘mineral’, 3691], [‘anatomical_structure’, 3642], [‘royal_family’, 3616], [‘warmian-masurian_voivodeship’, 3603], [‘podlaskie_voivodeship’, 3588], [‘canada’, 3550], [‘body_part’, 3505], [‘musical_composition_song’, 3496], [‘election’, 3433], [‘public_university’, 3432], [‘village_development_committee’,  3389], [‘wisconsin’, 3334], [‘razavi_khorasan_province’, 3322], [‘ohio’, 3315], [‘human_settlement’, 3231], [‘manager’, 3228], [‘unite_kingdom’, 3225], [‘academic_journal’, 3179], [‘someone’, 3164], [‘pomeranian_voivodeship’, 3145], [‘pennsylvania’, 3139], [‘west_virginia’, 3080], [‘england’, 3071], [‘minnesota’, 3034], [‘west_pomeranian_voivodeship’, 3033], [‘kuyavian-pomeranian_voivodeship’, 2979], [‘magazine’, 2975], [‘bridge’, 2954], [‘island’, 2935], [‘extend_play’, 2933], [‘civil_township’, 2916], [‘christian_bishop’, 2901], [‘indiana’, 2900], [‘illinois’, 2883], [‘studio_album’, 2862], [‘historic_build’, 2837], [‘texas’, 2827], [‘something’, 2806], [‘sale_contract’, 2797], [‘florida’, 2757], [‘china’, 2724], [‘-ite’, 2712], [‘you’, 2670], [‘india’, 2659], [‘airline’, 2658], [‘germany’, 2635], [‘cyclist’, 2618], [‘arachnid’, 2606], [‘museum’, 2590], [‘lorestan_province’, 2587], [‘commune_of_romania’, 2584], [‘oxygen’, 2577], [‘-er’, 2553], [‘saint’, 2553], [‘michigan’, 2505], [‘low_silesian_voivodeship’, 2503], [‘human’, 2487], [‘political_party’, 2485], [‘skyscraper’, 2483], [‘name’, 2458], [‘new_york_city’, 2453], [‘live_album’, 2449], [‘london’, 2443], [‘water’, 2440], [‘food’, 2377], [‘kerman_province’, 2368], [‘governor’, 2360], [‘president’, 2303], [‘australian_rule_football_player’, 2295], [‘game’, 2266], [‘wrestler’, 2254], [‘community_group’, 2223], [‘-like’, 2211], [‘bishop’, 2184], [‘website’, 2168], [‘\\xc5\\x9bwi\\xc4\\x99tokrzyskie_voivodeship’, 2147], [‘activity’, 2135], [‘crustacean’, 2091], [‘play’, 2086], [‘hospital’, 2086], [‘locomotive’, 2083], [‘private_university’, 2081], [‘action’, 2074], [‘martial_artist’, 2066], [‘public_transit_system’, 2056], [‘non-profit_organisation’, 2052], [‘village/n/united_states’, 2047], [‘monarch’, 2039], [‘mixed-sex_education’, 2034], [‘-less’, 2023], [‘gaelic_game_player’, 2022], [‘municipality_of_brazil’, 2021], [‘municipality_of_switzerland’, 2006], [‘give_name’, 1991], [‘government_agency’, 1990], [‘australia’, 1979], [‘moon’, 1941], [‘manga’, 1932], [‘comic_creator’, 1925], [‘gmina’, 1914], [‘less_poland_voivodeship’, 1911], [‘supreme_court_of_unite_state_case’, 1903], [‘legal_case’, 1897], [‘subsidiary’, 1892], [‘japan’, 1892], [‘france’, 1889], [‘record_label’, 1876], [‘president_of_organization’, 1872], [‘high_school’, 1860], [‘reservoir’, 1847], [‘boxer’, 1845], [‘shop_mall’, 1834], [‘compilation_album’, 1831], [‘golf_player’, 1830], [‘child’, 1816], [‘hydrogen’, 1811], [‘kentucky’, 1810], [‘ontario’, 1784], [‘tennis_player’, 1782], [‘congressman’, 1782], [‘virginia’, 1775], [‘journalist’, 1762], [‘horse’, 1755], [‘tamil_nadu’, 1733], [‘prime_minister’, 1733], [‘judge’, 1710], [‘hormozgan_province’, 1708], [‘castile_and_le\\xc3\\xb3n’, 1708], [‘dog’, 1707], [‘unite_state_representative’, 1690], [‘podkarpackie_voivodeship’, 1664], [‘iowa’, 1643], [‘time’, 1641], [‘mountain_range’, 1632], [‘work’, 1624], [‘south_khorasan_province’, 1617], [‘figure_skater’, 1615], [‘styria/n/slovenia’, 1608], [‘shop_center’, 1585], [‘district_of_peru’, 1580], [‘bone’, 1576], [‘park’, 1568], [‘low_carniola’, 1563], [‘music’, 1559], [‘house’, 1558], [‘anti-‘, 1550], [‘new_jersey’, 1545], [‘criminal’, 1539], [‘railway_line’, 1524], [‘tree’, 1524], [‘-able’, 1502], [‘oregon’, 1499], [‘kansa’, 1499], [‘spain’, 1497], [‘sound’, 1478], [‘central_province_sri_lanka’, 1475], [‘iron’, 1473], [‘man’, 1469], [‘-eth’, 1467], [‘protein_molecule’, 1465], [‘this’, 1463], [‘-est’, 1443], [‘municipality_of_spain’, 1443], [‘italy’, 1435], [‘wood’, 1419], [‘write’, 1413], [‘missouri’, 1409], [‘body’, 1406], [‘metal’, 1404], [‘cell’, 1403], [‘salt’, 1382], [‘dance’, 1381], [‘adult_actor’, 1350], [‘karnataka’, 1342], [‘light’, 1338], [‘crater’, 1332], [‘computer’, 1331], [‘woman’, 1329], [‘football_match’, 1325], [‘lubusz_voivodeship’, 1324], [‘paint’, 1322], [‘-y’, 1322], [‘eye’, 1313], [‘it’, 1306], [‘head’, 1297], [‘republika_srpska’, 1287], [‘lunar_crater’, 1278], [‘west_bengal’, 1277], [‘trade_union’, 1274], [‘silesian_voivodeship’, 1264], [‘i’, 1254], [‘non-profit_organization’, 1252], [‘money’, 1243], [‘color’, 1239], [‘municipality’, 1239], [‘cat’, 1236], [‘eat’, 1233], [‘model’, 1230], [‘wind’, 1223], [‘north_carolina’, 1221], [‘genus’, 1220], [‘philosopher’, 1208], [‘home’, 1201], [‘andhra_pradesh’, 1200], [‘flower’, 1200], [‘like’, 1199], [‘power_station’, 1196], [‘markazi_province’, 1186], [‘drink’, 1183], [‘musical’, 1179], [‘paper’, 1178], [‘good’, 1174], [‘product’, 1173], [‘los_angeles’, 1171], [‘opole_voivodeship’, 1167], [‘norway’, 1162], [‘municipality_of_mexico’, 1138], [‘race_car_driver’, 1131], [‘family’, 1131], [‘award’, 1128], [‘toronto’, 1125], [‘earth’, 1124], [‘sport_league’, 1116], [‘hand’, 1109], [‘washington_d._c’, 1101], [‘oklahoma’, 1100], [‘lighthouse’, 1092], [‘arkansas’, 1090], [‘point’, 1090], [‘massachusetts’, 1088], [‘township/n/pennsylvania’, 1088], [‘party’, 1079], [‘line’, 1075], [‘northeast_region_brazil’, 1073], [‘infantry’, 1070], [‘state’, 1068], [‘new_england_town’, 1059], [‘hotel’, 1054], [‘bed’, 1049], [‘mayor’, 1046], [‘plate’, 1045]]

If you want to do the same, here are some tips:

 

Just create a file named “foo.py” in your Mac’s “Documents” folder to contain this:
# === Step 1 begin
# File “foo.py” should contain this code
# Google(“python comments”) – https://docs.python.org/2/tutorial/introduction.html
# Comments are # for one-line, triple quotes for multi-line
print(“”)
print(“Step 1 begin”)

# Install Python – in Applications folder  on Mac
# Google (“python mac install”) – https://www.python.org/downloads/mac-osx/
# Download and install latest version – Latest Python 3 Release – Python 3.4.2

# Start IDLE – in Applications folder on Mac, under Python folder double-click IDLE
# In IDLE, type “import foo” and recall “foo.py” is in your Mac documents folder

import os

import string

print(“”)
print(“Step 1 complete”)
print(“Congratulations! You have Python installed, launched IDLE, and imported foo.py”)
# === Step 1 complete

# === Step 2 begin
# Building a dictionary of relationships and concepts
# MIT ConceptNet5 was downloaded as CSV files
print(“”)
print(“Step 2 begin”)

global path2assertions, dictrelations, dictconcepts, listrelations, listconcepts

path2assertions = “/Users/username/Documents/MyPythonFoo/MITConceptNet5_assertions”

def ac_step2(p):
“AC = Assertion Curate function”
global dictrelations, dictconcepts, listrelations, listconcepts

dictrelations = {}
dictconcepts = {}
listrelations = []
listconcepts = []

files = 0
Total_assertions = 0
English_assertions = 0

for i in os.listdir(p): # loop through CSV files in MITConceptNet5_assertion path p
y = p + “/” + i
if not(os.path.isfile(y)):
print(“Need to curate assertions”,y)
files = files + 1
ff = open(y, mode = ‘rb’)
try:
while True:
x = ff.readline()
Total_assertions = Total_assertions + 1
if x != b”:
x = repr(x)
y1 = “[”
y2 = “]”
x1 = x.find(y1)
x2 = x.find(y2)
z = x[x1:x2+1]
z1 = z.find(“/c/en/”)
z2 = z.rfind(“/c/en/”)
if z1 > 0:
if not z1 == z2:
English_assertions = English_assertions + 1
w1 = z.find(“,”)
w2 = z.rfind(“,”)
r = z[1:w1]
r = r[3:len(r)-1]
e1 = z[w1+1:w2]
e1 = e1[6:len(e1)-1]
e2 = z[w2+1:len(z)-1]
e2 = e2[6:len(e2)-1]
b = [r,e1,e2]
# print(b)
if r in dictrelations:
c = dictrelations[r]
dictrelations[r] = c + 1
else:
dictrelations[r] = 1
if e1 in dictconcepts:
c = dictconcepts[e1]
dictconcepts[e1] = c + 1
else:
dictconcepts[e1] = 1
if e2 in dictconcepts:
c = dictconcepts[e2]
dictconcepts[e2] = c + 1
else:
dictconcepts[e2] = 1
else:
break
except UnicodeDecodeError:
print(“UnicodeDecodeError:”, y)
print(“Files:”,files,”Total Assertions:”, Total_assertions, “English_assertions”, English_assertions)
ff.close()

# create list from dictionary, and then sort the list
for i in dictrelations:
listrelations.append([i,dictrelations[i]])
listrelations.sort(key=lambda n: n[1], reverse=True)
print(“”)
print(“Number of unique relations =”, len(listrelations))
print(“Top 50 relations =”, listrelations[0:50])
for i in dictconcepts:
listconcepts.append([i,dictconcepts[i]])
listconcepts.sort(key=lambda n: n[1], reverse=True)
print(“”)
print(“Number of unique concepts =”, len(listconcepts))
print(“Top 400 conscepts =”, listconcepts[0:400])

ac_step2(path2assertions)

print(“”)
print(“Step 2 complete”)
print(“Congratulations! The MIT ConceptNet5 CSV files looks good”)
print(“Checked Folder: MyPythonFoo/MITConceptNet5_assertions”)

# === Step 2 complete

When you run “foo.py” in Python IDLE it will generate the information I described above, showing the relations and the English concept.

Have fun!!!