Welcome to the Service Science worldwide community!

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

Cambridge Service Alliance

 Service Science and Service Researchers

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Follow Jim (@JimSpohrer) on Twitter

  About this site & registering.

Click here to access IBM’s University Community and SSME repository.

 

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’]
[‘IsA’, ‘hermosa_inn’, ‘hotel’]
[‘IsA’, ‘hilton_portland_hotel’, ‘hotel’]
[‘IsA’, ‘hilton_san_diego_bayfront’, ‘hotel’]
[‘IsA’, ‘hotel_ambacang’, ‘hotel’]
[‘IsA’, ‘hotel_astoria/n/copenhagen’, ‘hotel’]
[‘IsA’, ‘hotel_bringu\\xc3\\xa9′, ‘hotel’]
[‘IsA’, ‘hotel_bristol/n/oslo’, ‘hotel’]
[‘IsA’, ‘hotel_capri/n/havana’, ‘hotel’]
[‘IsA’, ‘hotel_casin\\xc3\\xb2_uaddan’, ‘hotel’]
[‘IsA’, ‘hotel_cirta’, ‘hotel’]
[‘IsA’, ‘hotel_congress’, ‘hotel’]
[‘IsA’, ‘hotel_icon’, ‘hotel’]
[‘IsA’, ‘hotel_le_majestic’, ‘hotel’]
[‘IsA’, ‘hotel_montgomery’, ‘hotel’]
[‘IsA’, ‘hotel_nikko_guam’, ‘hotel’]
[‘IsA’, ‘hotel_ross’, ‘hotel’]
[‘IsA’, ‘hotel_russell’, ‘hotel’]
[‘IsA’, ‘hotel_san_carlos/n/phoenix’, ‘hotel’]
[‘IsA’, ‘hotel_st._moritz’, ‘hotel’]
[‘IsA’, ‘hotel_tryp_habana_libre’, ‘hotel’]
[‘IsA’, ‘hotel_wangchuck’, ‘hotel’]
[‘IsA’, ‘hyatt_regency_hong_kong’, ‘hotel’]
[‘IsA’, ‘ibiza_gran_hotel’, ‘hotel’]
[‘IsA’, ‘imperial_golf_view_hotel’, ‘hotel’]
[‘IsA’, ‘jamaica_inn’, ‘hotel’]
[‘IsA’, ‘kampala_sheraton_hotel’, ‘hotel’]
[‘IsA’, ‘khanzad_hotel’, ‘hotel’]
[‘IsA’, ‘lae_international_hotel’, ‘hotel’]
[‘IsA’, ‘lanesborough’, ‘hotel’]
[‘IsA’, ‘le_m\\xc3\\xa9ridien_copacabana’, ‘hotel’]
[‘IsA’, ‘llao_llao_hotel’, ‘hotel’]
[‘IsA’, ‘mana_mana_beach_club’, ‘hotel’]
[‘IsA’, ‘mandarin_oriental_la_vega’, ‘hotel’]
[‘IsA’, ‘mandarin_oriental_sanya’, ‘hotel’]
[‘IsA’, ‘mandarin_oriental_tokyo’, ‘hotel’]
[‘IsA’, ‘mayag\\xc3\\xbcez_resort_casino’, ‘hotel’]
[‘IsA’, ‘meli\\xc3\\xa1_cohiba_hotel’, ‘hotel’]
[‘IsA’, ‘mi_ma/n/building’, ‘hotel’]
[‘IsA’, ‘millennium_hotel_mayfair’, ‘hotel’]
[‘IsA’, ‘mnawi_basha_hotel’, ‘hotel’]
[‘IsA’, ‘mondrian_hotel’, ‘hotel’]
[‘IsA’, ‘murray_hotel’, ‘hotel’]
[‘IsA’, ‘new_york_helmsley_hotel’, ‘hotel’]
[‘IsA’, ‘newport_arm_hotel’, ‘hotel’]
[‘IsA’, ‘nimb_hotel’, ‘hotel’]
[‘IsA’, ‘north_euston_hotel’, ‘hotel’]
[‘IsA’, ‘ouro_verde_hotel’, ‘hotel’]
[‘IsA’, ‘owain_glyndwr_hotel’, ‘hotel’]
[‘IsA’, ‘palazzo_versace_dubai’, ‘hotel’]
[‘IsA’, ‘palestine_hotel’, ‘hotel’]
[‘IsA’, ‘parsian_esteghlal_hotel’, ‘hotel’]
[‘IsA’, ‘pelangi_hotel/n/bintan’, ‘hotel’]
[‘IsA’, ‘proximity_hotel’, ‘hotel’]
[‘IsA’, ‘renaissance_chancery_court_hotel’, ‘hotel’]
[‘IsA’, ‘ritz-carlton_jakarta’, ‘hotel’]
[‘IsA’, ‘roosevelt_new_orleans_hotel’, ‘hotel’]
[‘IsA’, ’round_hill_jamaica’, ‘hotel’]
[‘IsA’, ‘royal_garden_hotel’, ‘hotel’]
[‘IsA’, ‘seaman_home/n/nuuk’, ‘hotel’]
[‘IsA’, ‘sheraton_montevideo’, ‘hotel’]
[‘IsA’, ‘sheraton_on_fall’, ‘hotel’]
[‘IsA’, ‘skirvin_hilton_hotel’, ‘hotel’]
[‘IsA’, ‘snowhill’, ‘hotel’]
[‘IsA’, ‘sofitel_chicago_water_tower’, ‘hotel’]
[‘IsA’, ‘st._regis_hotel’, ‘hotel’]
[‘IsA’, ‘st_david_hotel_spa’, ‘hotel’]
[‘IsA’, ‘stonewall_jackson_hotel’, ‘hotel’]
[‘IsA’, ‘taj_mahal_palace_tower’, ‘hotel’]
[‘IsA’, ‘tirana_international_hotel’, ‘hotel’]
[‘IsA’, ‘tryp_bellver’, ‘hotel’]
[‘IsA’, ‘windsor_hotel/n/montreal’, ‘hotel’]
[‘IsA’, ‘wotif.com’, ‘hotel’]
[‘IsA’, ‘yas_marina_hotel’, ‘hotel’]
[‘IsA’, ‘yosemite_lodge_at_fall’, ‘hotel’]
[‘IsA’, ’41_hotel’, ‘hotel’]
[‘IsA’, ‘adriatik_hotel’, ‘hotel’]
[‘IsA’, ‘amantaka’, ‘hotel’]
[‘IsA’, ‘apple_farm_inn/n/san_luis_obispo,_california’, ‘hotel’]
[‘IsA’, ‘baglioni_hotel’, ‘hotel’]
[‘IsA’, ‘big_bear_frontier’, ‘hotel’]
[‘IsA’, ‘capital_hilton’, ‘hotel’]
[‘IsA’, ‘casino_lisboa_macau’, ‘hotel’]
[‘IsA’, ‘chamran_grand_hotel’, ‘hotel’]
[‘IsA’, ‘christopher_hotel’, ‘hotel’]
[‘IsA’, ‘club_mahindra_holiday’, ‘hotel’]
[‘IsA’, ‘columbus_hotel_monaco’, ‘hotel’]
[‘IsA’, ‘copperhill_mountain_lodge’, ‘hotel’]
[‘IsA’, ‘craig-y-nos_castle’, ‘hotel’]
[‘IsA’, ‘ducor_hotel’, ‘hotel’]
[‘IsA’, ‘egerton_house_hotel’, ‘hotel’]
[‘IsA’, ‘el_castillo_hotel_fabrega_organizational_center’, ‘hotel’]
[‘IsA’, ‘enchant_garden_jamaica’, ‘hotel’]
[‘IsA’, ‘fairmont_orchid’, ‘hotel’]
[‘IsA’, ‘fairmont_palm_hotel_resort’, ‘hotel’]
[‘IsA’, ‘fairmont_san_jose’, ‘hotel’]
[‘IsA’, ‘first_world_hotel’, ‘hotel’]
[‘IsA’, ‘grand_hyatt_washington’, ‘hotel’]
[‘IsA’, ‘hale_koa_hotel’, ‘hotel’]
[‘IsA’, ‘halkin_hotel’, ‘hotel’]
[‘IsA’, ‘hilton_chicago’, ‘hotel’]
[‘IsA’, ‘hilton_niagara_fall_tower_2′, ‘hotel’]
[‘IsA’, ‘hilton_orlando_resort’, ‘hotel’]
[‘IsA’, ‘hong_kong_hilton’, ‘hotel’]
[‘IsA’, ‘hotel’, ‘large_build_with_many_bedroom’]
[‘IsA’, ‘hotel’, ‘lodge’]
[‘IsA’, ‘hotel’, ‘modern_shelter_construction’]
[‘IsA’, ‘hotel’, ‘service_company’]
[‘IsA’, ‘hotel_al_mehari’, ‘hotel’]
[‘IsA’, ‘hotel_arctic’, ‘hotel’]
[‘IsA’, ‘hotel_astoria_brussels’, ‘hotel’]
[‘IsA’, ‘hotel_del_coronado’, ‘hotel’]
[‘IsA’, ‘hotel_han_egede’, ‘hotel’]
[‘IsA’, ‘hotel_majestic/n/tunis’, ‘hotel’]
[‘IsA’, ‘hotel_metropole_brussels’, ‘hotel’]
[‘IsA’, ‘hotel_montesol’, ‘hotel’]
[‘IsA’, ‘hotel_pennsylvania’, ‘hotel’]
[‘IsA’, ‘hotel_ritsa’, ‘hotel’]
[‘IsA’, ‘hotel_saskatchewan’, ‘hotel’]
[‘IsA’, ‘hotel_windsor/n/melbourne’, ‘hotel’]
[‘IsA’, ‘hyatt_regency_chicago’, ‘hotel’]
[‘IsA’, ‘jw_marriott_jakarta’, ‘hotel’]
[‘IsA’, ‘jw_marriott_kuala_lumpur’, ‘hotel’]
[‘IsA’, ‘kampala_hilton_hotel’, ‘hotel’]
[‘IsA’, ‘king_edward_hotel/n/calgary’, ‘hotel’]
[‘IsA’, ‘le_meridien_hotel_piccadilly’, ‘hotel’]
[‘IsA’, ‘leonardo_plaza_hotel_jerusalem’, ‘hotel’]
[‘IsA’, ‘llanwenarth_house’, ‘hotel’]
[‘IsA’, ‘magnolia_hotel/n/houston’, ‘hotel’]
[‘IsA’, ‘malmaison_hotel_liverpool’, ‘hotel’]
[‘IsA’, ‘mandarin_oriental_miami’, ‘hotel’]
[‘IsA’, ‘manila_hotel’, ‘hotel’]
[‘IsA’, ‘mannings_heath_golf_club’, ‘hotel’]
[‘IsA’, ‘manor_house_hotel’, ‘hotel’]
[‘IsA’, ‘martha_washington_inn’, ‘hotel’]
[‘IsA’, ‘me_cancun’, ‘hotel’]
[‘IsA’, ‘michelangelo’, ‘hotel’]
[‘IsA’, ‘monte_rosa_hotel’, ‘hotel’]
[‘IsA’, ‘morgan_hotel’, ‘hotel’]
[‘IsA’, ‘motel’, ‘hotel’]
[‘IsA’, ‘palace_hotel_san_francisco’, ‘hotel’]
[‘IsA’, ‘palm_grandeur’, ‘hotel’]
[‘IsA’, ‘peninsula_hong_kong’, ‘hotel’]
[‘IsA’, ‘pierre’, ‘hotel’]
[‘IsA’, ‘prince_arthur_hotel’, ‘hotel’]
[‘IsA’, ‘qbic_hotel’, ‘hotel’]
[‘IsA’, ‘radisson_edwardian_hampshire_hotel’, ‘hotel’]
[‘IsA’, ‘radisson_sa_hotel_dubai_creek’, ‘hotel’]
[‘IsA’, ‘ritz-carlton_kuala_lumpur’, ‘hotel’]
[‘IsA’, ‘royal_albion_hotel’, ‘hotel’]
[‘IsA’, ‘runnymede_hotel’, ‘hotel’]
[‘IsA’, ‘san_domenico_house’, ‘hotel’]
[‘IsA’, ‘savoia_excelsior_palace’, ‘hotel’]
[‘IsA’, ‘savoy_hotel’, ‘hotel’]
[‘IsA’, ‘savoy_hotel/n/mussoorie’, ‘hotel’]
[‘IsA’, ‘sheraton_skyline_hotel_at_london_heathrow’, ‘hotel’]
[‘IsA’, ‘sport_hotel’, ‘hotel’]
[‘IsA’, ‘starhotels_anderson’, ‘hotel’]
[‘IsA’, ‘steigenberger_parkhotel_d\\xc3\\xbcsseldorf’, ‘hotel’]
[‘IsA’, ‘sunset_marquis_hotel’, ‘hotel’]
[‘IsA’, ‘sveti_stefan’, ‘hotel’]
[‘IsA’, ‘talbot_hotel/n/northamptonshire’, ‘hotel’]
[‘IsA’, ‘taschenbergpalais’, ‘hotel’]
[‘IsA’, ‘uzu_hotel’, ‘hotel’]
[‘IsA’, ‘venlaw’, ‘hotel’]
[‘IsA’, ‘white_swan_hotel_alnwick’, ‘hotel’]
[‘IsA’, ‘yukon_hotel’, ‘hotel’]
[‘IsA’, ’71_nyhavn’, ‘hotel’]
[‘IsA’, ‘alaskan_hotel_and_bar’, ‘hotel’]
[‘IsA’, ‘algonquin’, ‘hotel’]
[‘IsA’, ‘ananda_in_himalaya’, ‘hotel’]
[‘IsA’, ‘angsana_resort_spa’, ‘hotel’]
[‘IsA’, ‘antler_hotel/n/kingsland,_texas’, ‘hotel’]
[‘IsA’, ‘arizona_biltmore_hotel’, ‘hotel’]
[‘IsA’, ‘athenaeum_hotel’, ‘hotel’]
[‘IsA’, ‘baghdad_hotel’, ‘hotel’]
[‘IsA’, ‘barton_club_93′, ‘hotel’]
[‘IsA’, ‘beetham_tower_manchester’, ‘hotel’]
[‘IsA’, ‘bintan_lagoon_resort’, ‘hotel’]
[‘IsA’, ‘budget_suite_of_america’, ‘hotel’]
[‘IsA’, ‘cap_juluca_hotel’, ‘hotel’]
[‘IsA’, ‘captain_cook_hotel’, ‘hotel’]
[‘IsA’, ‘churston_court_inn’, ‘hotel’]
[‘IsA’, ‘claridge’, ‘hotel’]
[‘IsA’, ‘clinton_hotel_miami_beach’, ‘hotel’]
[‘IsA’, ‘crown_regency_hotel_and_tower’, ‘hotel’]
[‘IsA’, ‘crowne_plaza_hotel/n/lebanon’, ‘hotel’]
[‘IsA’, ‘david_citadel_hotel’, ‘hotel’]
[‘IsA’, ‘delano_hotel’, ‘hotel’]
[‘IsA’, ‘delta_bessborough’, ‘hotel’]
[‘IsA’, ‘detroit_riverside_hotel’, ‘hotel’]
[‘IsA’, ‘donovan_house’, ‘hotel’]
[‘IsA’, ‘double_jj_resort’, ‘hotel’]
[‘IsA’, ‘draycott_hotel’, ‘hotel’]
[‘IsA’, ‘dwarika_hotel’, ‘hotel’]
[‘IsA’, ‘eastland_park_hotel’, ‘hotel’]
[‘IsA’, ‘falaknuma_palace’, ‘hotel’]
[‘IsA’, ‘fanhams_hall’, ‘hotel’]
[‘IsA’, ‘four_season_baltimore_and_residence’, ‘hotel’]
[‘IsA’, ‘gaylord_palm_resort_convention_center’, ‘hotel’]
[‘IsA’, ‘george_washington_inn’, ‘hotel’]
[‘IsA’, ‘georgian_terrace_hotel’, ‘hotel’]
[‘IsA’, ‘glasshouse/n/hotel’, ‘hotel’]
[‘IsA’, ‘goldeneye/n/estate’, ‘hotel’]
[‘IsA’, ‘grand_hyatt_san_francisco’, ‘hotel’]
[‘IsA’, ‘hazlitt’, ‘hotel’]
[‘IsA’, ‘hermes_palace_hotel’, ‘hotel’]
[‘IsA’, ‘hilton_anaheim’, ‘hotel’]
[‘IsA’, ‘hilton_hawaiian_village’, ‘hotel’]
[‘IsA’, ‘hilton_new_york’, ‘hotel’]
[‘IsA’, ‘hilton_prague’, ‘hotel’]
[‘IsA’, ‘hilton_princess_san_salvador_hotel’, ‘hotel’]
[‘IsA’, ‘hilton_san_francisco_union_square’, ‘hotel’]
[‘IsA’, ‘hong_kong_gold_coast_hotel’, ‘hotel’]
[‘IsA’, ‘hong_kong_hotel’, ‘hotel’]
[‘IsA’, ‘hotel’, ‘place_to_stay_when_you_be_away_from_home’]
[‘IsA’, ‘hotel_abkhazia_sokhumi’, ‘hotel’]
[‘IsA’, ‘hotel_andaluz’, ‘hotel’]
[‘IsA’, ‘hotel_astoria/n/saint_petersburg’, ‘hotel’]
[‘IsA’, ‘hotel_bellevue_palace’, ‘hotel’]
[‘IsA’, ‘hotel_dajti’, ‘hotel’]
[‘IsA’, ‘hotel_ibis_alger_aeroport’, ‘hotel’]
[‘IsA’, ‘hotel_jugoslavija’, ‘hotel’]
[‘IsA’, ‘hotel_moskva/n/belgrade’, ‘hotel’]
[‘IsA’, ‘hotel_motithang’, ‘hotel’]
[‘IsA’, ‘hotel_paracas’, ‘hotel’]
[‘IsA’, ‘hotel_petersberg’, ‘hotel’]
[‘IsA’, ‘hotel_vi_jahreszeiten_kempinski’, ‘hotel’]
[‘IsA’, ‘hyatt_regency_dushanbe_hotel’, ‘hotel’]
[‘IsA’, ‘islander_hotel’, ‘hotel’]
[‘IsA’, ‘izmailovo_hotel’, ‘hotel’]
[‘IsA’, ‘jason_travel_media’, ‘hotel’]
[‘IsA’, ‘kampala_serena_hotel’, ‘hotel’]
[‘IsA’, ‘kempinski_residence_palm_jumeirah’, ‘hotel’]
[‘IsA’, ‘kyoto_grand_hotel_and_garden’, ‘hotel’]
[‘IsA’, ‘l_enfant_plaza_hotel’, ‘hotel’]
[‘IsA’, ‘luton_hoo’, ‘hotel’]
[‘IsA’, ‘malmaison_hotel_read’, ‘hotel’]
[‘IsA’, ‘mandarin_oriental_munich’, ‘hotel’]
[‘IsA’, ‘mark_hopkins_hotel’, ‘hotel’]
[‘IsA’, ‘millennium_bailey_hotel’, ‘hotel’]
[‘IsA’, ‘nanning_marriott’, ‘hotel’]
[‘IsA’, ‘nh_gran_hotel_provincial’, ‘hotel’]
[‘IsA’, ‘novotel_nathan_road_kowloon_hong_kong’, ‘hotel’]
[‘IsA’, ‘omni_dallas_hotel’, ‘hotel’]
[‘IsA’, ‘omphoy_ocean_resort’, ‘hotel’]
[‘IsA’, ‘peabody_hotel’, ‘hotel’]
[‘IsA’, ‘pioneer_hotel’, ‘hotel’]
[‘IsA’, ‘plaza_resort_bonaire’, ‘hotel’]
[‘IsA’, ‘queen_elizabeth_hotel’, ‘hotel’]
[‘IsA’, ‘radisson_blu_iveria_hotel_tbilisi’, ‘hotel’]
[‘IsA’, ‘roosevelt_hotel/n/new_york’, ‘hotel’]
[‘IsA’, ‘royal_dokmaideng_hotel’, ‘hotel’]
[‘IsA’, ‘scotsman_hotel’, ‘hotel’]
[‘IsA’, ‘sevilla_hotel’, ‘hotel’]
[‘IsA’, ‘sheraton_oran_hotel_and_tower’, ‘hotel’]
[‘IsA’, ‘star_city_casino’, ‘hotel’]
[‘IsA’, ‘swiss\\xc3\\xb4tel_nankai_osaka’, ‘hotel’]
[‘IsA’, ‘ten_square’, ‘hotel’]
[‘IsA’, ‘tide_inn’, ‘hotel’]
[‘IsA’, ‘viva_hotel_and_resort’, ‘hotel’]
[‘IsA’, ‘waldorf_hilton’, ‘hotel’]
[‘IsA’, ‘water_club’, ‘hotel’]
[‘IsA’, ‘westin_seattle’, ‘hotel’]
[‘IsA’, ‘aleksandar_palas_hotel’, ‘hotel’]
[‘IsA’, ‘allegro_papagayo’, ‘hotel’]
[‘IsA’, ‘american_colony_hotel’, ‘hotel’]
[‘IsA’, ‘amsterdam_hilton_hotel’, ‘hotel’]
[‘IsA’, ‘atlanta_marriott_marquis’, ‘hotel’]
[‘IsA’, ‘balmoral_hotel’, ‘hotel’]
[‘IsA’, ‘ban_pako’, ‘hotel’]
[‘IsA’, ‘bed_and_breakfast’, ‘hotel’]
[‘IsA’, ‘bella_sky_hotel’, ‘hotel’]
[‘IsA’, ‘breidenbacher_hof’, ‘hotel’]
[‘IsA’, ‘british_colonial_hilton_nassau’, ‘hotel’]
[‘IsA’, ‘broad_street_tower’, ‘hotel’]
[‘IsA’, ‘brown_hotel’, ‘hotel’]
[‘IsA’, ‘canad_inn’, ‘hotel’]
[‘IsA’, ‘chase_park_plaza_hotel’, ‘hotel’]
[‘IsA’, ‘chewton_glen’, ‘hotel’]
[‘IsA’, ‘colcord_hotel’, ‘hotel’]
[‘IsA’, ‘copacabana_palace’, ‘hotel’]
[‘IsA’, ‘copley_square_hotel’, ‘hotel’]
[‘IsA’, ‘corinthia_hotel_london’, ‘hotel’]
[‘IsA’, ‘cork_international_airport_hotel’, ‘hotel’]
[‘IsA’, ‘courtyard_by_marriott_gurgaon’, ‘hotel’]
[‘IsA’, ‘crieff_hydro’, ‘hotel’]
[‘IsA’, ‘crowne_plaza_niagara_fall_fallsview’, ‘hotel’]
[‘IsA’, ‘duke_of_cornwall_hotel’, ‘hotel’]
[‘IsA’, ‘eden_h_real_arena_hotel’, ‘hotel’]
[‘IsA’, ‘fairmont_copley_plaza_hotel’, ‘hotel’]
[‘IsA’, ‘fairmont_hamilton_princess’, ‘hotel’]
[‘IsA’, ‘frenchman_cove_resort’, ‘hotel’]
[‘IsA’, ‘galt_house’, ‘hotel’]
[‘IsA’, ‘gleneagles_hotel’, ‘hotel’]
[‘IsA’, ‘gramercy_park_hotel’, ‘hotel’]
[‘IsA’, ‘gran_hotel_bali’, ‘hotel’]
[‘IsA’, ‘grand_hotel_kathmandu’, ‘hotel’]
[‘IsA’, ‘grand_hotel_vienna’, ‘hotel’]
[‘IsA’, ‘grand_hyatt_muscat_hotel’, ‘hotel’]
[‘IsA’, ‘grand_hyatt_seoul’, ‘hotel’]
[‘IsA’, ‘grand_palace_hotel_riga’, ‘hotel’]
[‘IsA’, ‘hempel_hotel’, ‘hotel’]
[‘IsA’, ‘henderson_village’, ‘hotel’]
[‘IsA’, ‘hilton_waterfront_beach_resort’, ‘hotel’]
[‘IsA’, ‘hollenden_hotel’, ‘hotel’]
[‘IsA’, ‘hotel_alexandra’, ‘hotel’]
[‘IsA’, ‘hotel_bossert’, ‘hotel’]
[‘IsA’, ‘hotel_giraffe’, ‘hotel’]
[‘IsA’, ‘hotel_impala’, ‘hotel’]
[‘IsA’, ‘hotel_plaza_grande’, ‘hotel’]
[‘IsA’, ‘hotel_senator/n/saskatoon’, ‘hotel’]
[‘IsA’, ‘hotel_tajikistan’, ‘hotel’]
[‘IsA’, ‘hotel_vancouver’, ‘hotel’]
[‘IsA’, ‘imperial_resort_beach_hotel’, ‘hotel’]
[‘IsA’, ‘inbal_jerusalem_hotel’, ‘hotel’]
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[‘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!!!

Intro Talk and Some Resources

This talk will provide a very brief introduction to service science and service-dominant logic. A historical perspective on the importance of service and service innovation will be followed by a discussion of (1) ways of thinking about value, and (2) ways of thinking about the future of service.   The International Society of Service Innovation Professionals (pronounced I-ZIP) is a non-profit professional association that provides access to a network of people and free resources to help students, faculty, practitioners, and other professionals learn about Service Innovation from a Service Science and Service-Dominant Logic perspective.   To improve value co-creation in existing service systems, it is helpful to understand how groups use practical tools such as Value Network Mapping and Analysis.   To inspire the design of new service innovations and value co-creation mechanisms, it is helpful to understand important technology, business, and societal trends, such as cognitive systems.
Additional Resources:
Presentation:
http://www.slideshare.net/spohrer/2030-inspire-students-to-build-it-better-20150113-v3

Service Science Blog website:
http://www.service-science.info
Service Dominant Logic website:
http://www.sdlogic.net/
Practical Tool (OnLine Book): Thinking About Value with Value Network Analysis (Verne Allee)
http://www.valuenetworksandcollaboration.com/home/tableofcontents.html

Example Technology Trend Discussion – Cognitive Systems
https://www.linkedin.com/groups/Cognitive-Systems-Institute-6729452

Example Technology Trend Website – Cognitive Systems
http://www.cognitive-science.info
ISSIP website:
http://www.issip.org

ISSIP Discussion:
https://www.linkedin.com/groups/International-Society-Service-Innovation-Professionals-4720974

Join ISSIP (Free) – International Society of Service Innovation Professionals
http://www.issip.org/wp-login.php?action=register

NIST: Global City Teams Challenge – Tech Jam (IoT Opportunity)

Prof. Steve Kwan (SJSU) alerted me to this opportunity:

 

Hello All -

The Global City Teams Challenge is an initiative designed to advance the deployment of Internet of Things (IoT) technologies within a smart city / smart community environment. More than 30 teams are pursuing projects related to sectors including public safety, energy and transportation. Participants in the Global City Teams Challenge are working to deploy an emerging technology within a cyber-physical system (CPS) by June 2015.

The Tech Jam will provide:

  1. Existing GCTC participants with an opportunity to present their project plans and identify additional project partners.
  2. An opportunity for entities not yet participating in the Challenge to explore a new project idea and/or identify partners and develop a new Action Clusters.
  3. Attendees with an opportunity to hear from government agencies on funding programs relevent to GCTC participants and IoT/CPS/Smart Cities more generally.
  4. An opportunity to hear from global leaders and experts of IoT/CPS/Smart Cities.

Who Should Attend the Tech Jam?

  • Global City Teams Challenge participants
  • Attendees from the September 2014 Workshop
  • Potential new Challenge participants with IoT/CPS technologies and designs that are directly relevant to the Challenge’s objectives
  • Mayors, CIOs, CTOs, Innovation Directors, Managers from local, state, federal governments working on smart city deployments
  • Corporations, educational institutions, non-profits working on smart city projects
  • Anyone interested in the latest trends and standards in IoT/CPS and Smart Cities

To register for Tech Jam click here.To learn more about the Global City Teams Challenge visit our website for more information about the Challenge. Have questions about the Challenge or the Tech Jam, please email sokwoo.rhee@nist.gov or william.maguire@us-ignite.org.

Best regards,

Sokwoo Rhee
Associate Director, Cyber-Physical Systems
National Institute of Standards and Technology

ICServ2015: July 7-9, San Jose, CA USA

Hopeing to see you at ICServ 2015.

Please take 30 minutes to request that three colleagues submit an abstract to ICServ 2015 before Jan 18th deadline…
Please submit your abstract and/or paper through the Online Conference System (OCS) powered by Springer: http://ocs.springer.com/ocs/home/ICServ2015

You can use the information below to promote our conference before the abstract deadline on 18 January – thanks!

***
Conference: The 3rd international conference on Serviceology (ICServ 2015) will be held for July 7 – 9, 2015 in San Jose, CA, USA

Theme: Engineering and Management of Smart Service Systems – Cultural Factors in Customer Engagement

The 3rd international conference on Serviceology (ICServ 2015) will be held for July 7 – 9, 2015 in San Jose, CA, USA. It is the first meeting held outside of Japan. The main goal of this conference is to provide opportunities for researchers from academia and industry to share the latest technologies, methodologies, and case studies toward co-creation of services in a sustainable society. ICServ 2015 will run just before Frontiers in Service, the pioneer conference in management of service, which will be held July 9 – 12 at the same venue.

ICServ home page:  http://icserv2015.serviceology.org/html/home.html
Call for papers:  http://icserv2015.serviceology.org/CfP_ICServ2015V5.pdf
Reminder on important dates: http://icserv2015.serviceology.org/html/important_dates.html
Submit abstract and/or paper here: http://ocs.springer.com/ocs/home/ICServ2015

Please consider submitting an abstract and attending this conference. I encourage you to share this invitation with your networks.
***

Universities becoming the startup engines of their regions

VCIC –  Venture Capital Investment Competition
http://www.vcic.org/

VCIC is very interesting, and I did not know about them.  I found this especially interesting:
“Our judges are venture capitalists, who come to VCIC for the opportunity to reconnect with their alma maters,
network with other VCs and get a peek at some early stage startups as well as bright MBAs.”

Here are some of the related or complementary companies that I am tracking:
http://www.skild.com/
http://ninesigma.com/
http://www.realworlddesignchallenge.org/
https://www.mindsumo.com/
http://www.kaggle.com/
http://www.ncet2.org/
http://www.globalcorporateventuring.com/pages/triple-helix-venturing-for-the-longer-term.html
http://sites.nationalacademies.org/pga/uidp/index.htm

Kickstarter is being embraced by many universities and student entrepreneurship groups:
https://www.kickstarter.com/pages/duke
http://www.sandiego.edu/about/news_center/news/news_detail.php?_focus=47965
http://c21u.gatech.edu/blog/kickstarter-new-platform-higher-education-innovation

AUTM has been ranking universities based on local start-up impact on  job market and tax base growth:
        http://www.autm.net/Home.htm
        Old & Suprising Example of AUTM Ranking: http://www.unews.utah.edu/old/p/121710-1.html
        Meanwhile Stanford and MIT battle it out at the top: http://www.forbes.com/sites/petercohan/2012/11/06/stanfords-2-7-trillion-economic-jolt-beats-mits-2-trillion/

Professional Association (IEEE, ACM, INFORMS, AAAI, AIS,  ISSIP, IIE, INCOSE, etc.) are doing more to encourage entrepreneurship linking their senior members and student members:
http://www.ieee.org/education_careers/education/university_programs/smarterplanetchallenge.html
http://en.wikipedia.org/wiki/ACM_International_Collegiate_Programming_Contest

And of course IBM has some relevant partnerships and programs for them.
http://smartercitieschallenge.org/
http://ibmsmartcamp.com/

Previously, I had written about some of these here:
Service System Analytics: http://service-science.info/archives/2177
How can universities win the race with ever smarter machines: http://service-science.info/archives/2558
Tip: Starting a new university competition: http://service-science.info/archives/2538
California leading a transformation of higher education: http://service-science.info/archives/2692
NSF Virtual Forum: Smart Service Systems: http://service-science.info/archives/3209

If students need a professional association, I recommend ISSIP.org.  Students can join ISSIP.org (free to join here) and participate in ISSIP mentoring projects: http://service-science.info/archives/3084

Serviciology – Service Terminology and Service Taxonomy

A proposal for establishing the serviciology, i.e. the science & the teaching about the service as such, has been compiled at end of the year 2014. It has been explained & illustrated in the slide deck below.
http://de.slideshare.net/PaulGHz/serviciology-service-terminology-and-service-taxonomy-v010000

By systematically developing & permanently establishing the discipline of serviciology shall be created the terminological & conceptual, methodical & practical foundations for reliable & cost-efficient service providing management (= servuction management).

Part 01 of this venture deals with

  • the service terminology, starting with the derivation & definition of the term ‘service’
  • the service characteristics that must be comprehensively allowed for
  • the service consumer as the mission critical role for any & every service rendering
  • the identification of service types with its basics & method
  • the specification of service quality with its basics & method
  • the service taxonomy for categorizing different service types
  • the service providing modell comprising
  • >> the 4 main roles & their interactions
  • >> the servuction environment & the servuction process

Based on the feedbacks & comments, incitements & suggestions, corrections & complements out of the community, this fundamental part will be advanced & detailed, completed & improved. Further parts of the serviciology will be worked out & framed in appropriate documentations.