{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T05:04:52Z","timestamp":1755839092668,"version":"3.41.0"},"reference-count":32,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2020,6,1]],"date-time":"2020-06-01T00:00:00Z","timestamp":1590969600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGIR Forum"],"published-print":{"date-parts":[[2020,6]]},"abstract":"<jats:p>The SUM'20 workshop was held at the 13th ACM International WSDM Conference on Web Search and Data Mining (WSDM 2020) in Houston, Texas. The purpose of the workshop was to stimulate the research community to explore open challenges in building systems that can capture the user's state, context and goals, as well as effectively use these for leveraging intelligent user-centric systems in a wide range of applications. The workshop incorporated different plenary sessions and contributed talks. The workshop website and proceedings are available at https:\/\/www.k4all.org\/event\/wsdmsum20.<\/jats:p>","DOI":"10.1145\/3451964.3451969","type":"journal-article","created":{"date-parts":[[2021,2,21]],"date-time":"2021-02-21T01:42:58Z","timestamp":1613871778000},"page":"1-11","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Report on the WSDM 2020 workshop on state-based user modelling (SUM'20)"],"prefix":"10.1145","volume":"54","author":[{"given":"Sahan","family":"Bulathwela","sequence":"first","affiliation":[{"name":"University College London, London, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mar\u00eda","family":"P\u00e9rez-Ortiz","sequence":"additional","affiliation":[{"name":"University College London, London, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rishabh","family":"Mehrotra","sequence":"additional","affiliation":[{"name":"Spotify Research, London, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Davor","family":"Orlic","sequence":"additional","affiliation":[{"name":"Knowledge 4 All Foundation, London, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Colin","family":"de la Higuera","sequence":"additional","affiliation":[{"name":"Nantes University, Nantes, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John","family":"Shawe-Taylor","sequence":"additional","affiliation":[{"name":"University College London, London, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emine","family":"Yilmaz","sequence":"additional","affiliation":[{"name":"University College London, London, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,2,19]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3295750.3298934"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3027063.3053175"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2019.02.046"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/325737.325872"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.5555\/2969239.2969296"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080835"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-85820-3_7"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2016.04.020"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939746"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/2911451.2911542"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.5555\/3104322.3104326"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3320496.3320500"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3298689.3347028"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3274784.3274788"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308560.3320087"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-31454-4_14"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380281"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3358047"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3358048"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343413.3377974"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343413.3378009"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331260"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380071"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331187"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080823"},{"key":"e_1_2_1_27_1","volume-title":"AAAI Conference on Artificial Intelligence, AAAI '20","author":"Bulathwela Sahan","year":"2020","unstructured":"Sahan Bulathwela , Maria Perez-Ortiz , Emine Yilmaz , and John Shawe-Taylor . Towards an integrative educational recommender for lifelong learners . In AAAI Conference on Artificial Intelligence, AAAI '20 , 2020 a. Sahan Bulathwela, Maria Perez-Ortiz, Emine Yilmaz, and John Shawe-Taylor. Towards an integrative educational recommender for lifelong learners. In AAAI Conference on Artificial Intelligence, AAAI '20, 2020a."},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3133098"},{"key":"e_1_2_1_29_1","volume-title":"AAAI Conference on Artificial Intelligence, AAAI '20","author":"Bulathwela Sahan","year":"2020","unstructured":"Sahan Bulathwela , Maria Perez-Ortiz , Emine Yilmaz , and John Shawe-Taylor . Truelearn : A family of bayesian algorithms to match lifelong learners to open educational resources . In AAAI Conference on Artificial Intelligence, AAAI '20 , 2020 b. Sahan Bulathwela, Maria Perez-Ortiz, Emine Yilmaz, and John Shawe-Taylor. Truelearn: A family of bayesian algorithms to match lifelong learners to open educational resources. In AAAI Conference on Artificial Intelligence, AAAI '20, 2020b."},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3379336.3381457"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371883"},{"key":"e_1_2_1_32_1","volume-title":"Sage: Interactive state-aware point-of-interest recommendation","author":"Omidvar-Tehrani Behrooz","year":"2020","unstructured":"Behrooz Omidvar-Tehrani , Sruthi Viswanathan , Frederic Roulland , and Jean-Michel Renders . Sage: Interactive state-aware point-of-interest recommendation , 2020 . Workshop on State-Based User Modelling (SUM '20) at 13th ACM International Conference on Web Search and Data Mining , https:\/\/www.k4all.org\/wp-content\/uploads\/2020\/01\/WSDMSUM20_paper_SAGE_Interactive_State_aware-Point_of_Interest_Recommendation.pdf. Behrooz Omidvar-Tehrani, Sruthi Viswanathan, Frederic Roulland, and Jean-Michel Renders. Sage: Interactive state-aware point-of-interest recommendation, 2020. Workshop on State-Based User Modelling (SUM '20) at 13th ACM International Conference on Web Search and Data Mining, https:\/\/www.k4all.org\/wp-content\/uploads\/2020\/01\/WSDMSUM20_paper_SAGE_Interactive_State_aware-Point_of_Interest_Recommendation.pdf."},{"key":"e_1_2_1_33_1","volume-title":"Scalable psychological momentum estimation in e-sports","author":"White Alfonso","year":"2020","unstructured":"Alfonso White and Daniela M. Romano . Scalable psychological momentum estimation in e-sports , 2020 . Workshop on State-Based User Modelling (SUM '20) at 13th ACM International Conference on Web Search and Data Mining , https:\/\/www.k4all.org\/wp-content\/uploads\/2020\/01\/WSDMSUM20_paper_Scalable_Psychological_Momentum_Forecasting_in_Esports.pdf. Alfonso White and Daniela M. Romano. Scalable psychological momentum estimation in e-sports, 2020. Workshop on State-Based User Modelling (SUM '20) at 13th ACM International Conference on Web Search and Data Mining, https:\/\/www.k4all.org\/wp-content\/uploads\/2020\/01\/WSDMSUM20_paper_Scalable_Psychological_Momentum_Forecasting_in_Esports.pdf."}],"container-title":["ACM SIGIR Forum"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3451964.3451969","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3451964.3451969","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:03:00Z","timestamp":1750197780000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3451964.3451969"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6]]},"references-count":32,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,6]]}},"alternative-id":["10.1145\/3451964.3451969"],"URL":"https:\/\/doi.org\/10.1145\/3451964.3451969","relation":{},"ISSN":["0163-5840"],"issn-type":[{"type":"print","value":"0163-5840"}],"subject":[],"published":{"date-parts":[[2020,6]]},"assertion":[{"value":"2021-02-19","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}