{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T02:39:43Z","timestamp":1743129583231,"version":"3.40.3"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030129804"},{"type":"electronic","value":"9783030129811"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-12981-1_2","type":"book-chapter","created":{"date-parts":[[2019,2,6]],"date-time":"2019-02-06T11:59:55Z","timestamp":1549454395000},"page":"17-32","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Collaborative Thompson Sampling"],"prefix":"10.1007","author":[{"given":"Zhenyu","family":"Zhu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liusheng","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongli","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,2,7]]},"reference":[{"key":"2_CR1","doi-asserted-by":"crossref","unstructured":"Agarwal, D., Long, B., Traupman, J., Xin, D., Zhang, L.: Laser: a scalable response prediction platform for online advertising. In: Proceedings of the 7th ACM International Conference on Web Search and Data Mining, pp. 173\u2013182. ACM (2014)","DOI":"10.1145\/2556195.2556252"},{"key":"2_CR2","unstructured":"Agrawal, S., Goyal, N.: Analysis of Thompson sampling for the multi-armed bandit problem. In: Conference on Learning Theory, pp. 39.1\u201339.26 (2012)"},{"key":"2_CR3","unstructured":"Agrawal, S., Goyal, N.: Thompson sampling for contextual bandits with linear payoffs. In: International Conference on Machine Learning, pp. 127\u2013135 (2013)"},{"key":"2_CR4","doi-asserted-by":"crossref","unstructured":"Banerjee, A.: On Bayesian bounds. In: Proceedings of the 23rd International Conference on Machine Learning, pp. 81\u201388. ACM (2006)","DOI":"10.1145\/1143844.1143855"},{"key":"2_CR5","unstructured":"Bresler, G., Chen, G.H., Shah, D.: A latent source model for online collaborative filtering. In: Advances in Neural Information Processing Systems, pp. 3347\u20133355 (2014)"},{"key":"2_CR6","doi-asserted-by":"crossref","unstructured":"Brod\u00e9n, B., Hammar, M., Nilsson, B.J., Paraschakis, D.: Ensemble recommendations via Thompson sampling: an experimental study within e-Commerce. In: 23rd International Conference on Intelligent User Interfaces, pp. 19\u201329. ACM (2018)","DOI":"10.1145\/3172944.3172967"},{"key":"2_CR7","unstructured":"Chapelle, O., Li, L.: An empirical evaluation of Thompson sampling. In: Advances in Neural Information Processing Systems, pp. 2249\u20132257 (2011)"},{"key":"2_CR8","doi-asserted-by":"publisher","first-page":"612","DOI":"10.1137\/1.9781611975321.69","volume-title":"Proceedings of the 2018 SIAM International Conference on Data Mining","author":"Konstantina Christakopoulou","year":"2018","unstructured":"Christakopoulou, K., Banerjee, A.: Learning to interact with users: a collaborative-bandit approach. In: Proceedings of the 2018 SIAM International Conference on Data Mining, pp. 612\u2013620. SIAM (2018)"},{"key":"2_CR9","unstructured":"Chu, W., Li, L., Reyzin, L., Schapire, R.: Contextual bandits with linear payoff functions. In: Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, pp. 208\u2013214 (2011)"},{"key":"2_CR10","doi-asserted-by":"crossref","unstructured":"Chu, W., et al.: A case study of behavior-driven conjoint analysis on Yahoo!: front page today module. In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1097\u20131104. ACM (2009)","DOI":"10.1145\/1557019.1557138"},{"key":"2_CR11","doi-asserted-by":"crossref","unstructured":"Ferreira, K., Simchi-Levi, D., Wang, H.: Online network revenue management using Thompson sampling (2017)","DOI":"10.1287\/opre.2018.1755"},{"issue":"3","key":"2_CR12","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1038\/s41562-018-0297-4","volume":"2","author":"CM Glaze","year":"2018","unstructured":"Glaze, C.M., Filipowicz, A.L., Kable, J.W., Balasubramanian, V., Gold, J.I.: A bias-variance trade-off governs individual differences in on-line learning in an unpredictable environment. Nat. Hum. Behav. 2(3), 213 (2018)","journal-title":"Nat. Hum. Behav."},{"key":"2_CR13","unstructured":"Gopalan, A., Mannor, S.: Thompson sampling for learning parameterized Markov decision processes. In: Conference on Learning Theory, pp. 861\u2013898 (2015)"},{"key":"2_CR14","unstructured":"Gopalan, A., Mannor, S., Mansour, Y.: Thompson sampling for complex online problems. In: International Conference on Machine Learning, pp. 100\u2013108 (2014)"},{"key":"2_CR15","unstructured":"Graepel, T., Candela, J.Q., Borchert, T., Herbrich, R.: Web-scale Bayesian click-through rate prediction for sponsored search advertising in Microsoft\u2019s Bing search engine. Omnipress (2010)"},{"key":"2_CR16","unstructured":"Johnson, C.C.: Logistic matrix factorization for implicit feedback data. In: Advances in Neural Information Processing Systems, vol. 27 (2014)"},{"key":"2_CR17","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1007\/978-3-642-34106-9_18","volume-title":"Algorithmic Learning Theory","author":"E Kaufmann","year":"2012","unstructured":"Kaufmann, E., Korda, N., Munos, R.: Thompson sampling: an asymptotically optimal finite-time analysis. In: Bshouty, N.H., Stoltz, G., Vayatis, N., Zeugmann, T. (eds.) ALT 2012. LNCS (LNAI), vol. 7568, pp. 199\u2013213. Springer, Heidelberg (2012). \n                    https:\/\/doi.org\/10.1007\/978-3-642-34106-9_18"},{"key":"2_CR18","unstructured":"Kawale, J., Bui, H.H., Kveton, B., Tran-Thanh, L., Chawla, S.: Efficient Thompson sampling for online matrix-factorization recommendation. In: Advances in Neural Information Processing Systems, pp. 1297\u20131305 (2015)"},{"key":"2_CR19","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1016\/j.csda.2015.08.001","volume":"94","author":"F Lavancier","year":"2016","unstructured":"Lavancier, F., Rochet, P.: A general procedure to combine estimators. Comput. Stat. Data Anal. 94, 175\u2013192 (2016)","journal-title":"Comput. Stat. Data Anal."},{"key":"2_CR20","doi-asserted-by":"crossref","unstructured":"Li, L., Chu, W., Langford, J., Schapire, R.E.: A contextual-bandit approach to personalized news article recommendation. In: Proceedings of the 19th International Conference on World Wide Web, pp. 661\u2013670. ACM (2010)","DOI":"10.1145\/1772690.1772758"},{"key":"2_CR21","doi-asserted-by":"crossref","unstructured":"Li, S., Karatzoglou, A., Gentile, C.: Collaborative filtering bandits. In: Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 539\u2013548. ACM (2016)","DOI":"10.1145\/2911451.2911548"},{"key":"2_CR22","doi-asserted-by":"crossref","unstructured":"Nguyen, T.T., Lauw, H.W.: Dynamic clustering of contextual multi-armed bandits. In: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, pp. 1959\u20131962. ACM (2014)","DOI":"10.1145\/2661829.2662063"},{"key":"2_CR23","unstructured":"Ouyang, Y., Gagrani, M., Nayyar, A., Jain, R.: Learning unknown Markov decision processes: a Thompson sampling approach. In: Advances in Neural Information Processing Systems, pp. 1333\u20131342 (2017)"},{"issue":"1","key":"2_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1561\/2200000070","volume":"11","author":"DJ Russo","year":"2018","unstructured":"Russo, D.J., Van Roy, B., Kazerouni, A., Osband, I., Wen, Z., et al.: A tutorial on Thompson sampling. Found. Trends\u00ae in Mach. Learn. 11(1), 1\u201396 (2018)","journal-title":"Found. Trends\u00ae in Mach. Learn."},{"issue":"4","key":"2_CR25","doi-asserted-by":"publisher","first-page":"500","DOI":"10.1287\/mksc.2016.1023","volume":"36","author":"EM Schwartz","year":"2017","unstructured":"Schwartz, E.M., Bradlow, E.T., Fader, P.S.: Customer acquisition via display advertising using multi-armed bandit experiments. Mark. Sci. 36(4), 500\u2013522 (2017)","journal-title":"Mark. Sci."},{"issue":"6","key":"2_CR26","doi-asserted-by":"publisher","first-page":"639","DOI":"10.1002\/asmb.874","volume":"26","author":"SL Scott","year":"2010","unstructured":"Scott, S.L.: A modern Bayesian look at the multi-armed bandit. Appl. Stoch. Models Bus. Ind. 26(6), 639\u2013658 (2010)","journal-title":"Appl. Stoch. Models Bus. Ind."},{"issue":"3\/4","key":"2_CR27","doi-asserted-by":"publisher","first-page":"285","DOI":"10.2307\/2332286","volume":"25","author":"WR Thompson","year":"1933","unstructured":"Thompson, W.R.: On the likelihood that one unknown probability exceeds another in view of the evidence of two samples. Biometrika 25(3\/4), 285\u2013294 (1933)","journal-title":"Biometrika"},{"issue":"4","key":"2_CR28","doi-asserted-by":"publisher","first-page":"791","DOI":"10.1093\/biomet\/80.4.791","volume":"80","author":"R Wolfinger","year":"1993","unstructured":"Wolfinger, R.: Laplace\u2019s approximation for nonlinear mixed models. Biometrika 80(4), 791\u2013795 (1993)","journal-title":"Biometrika"},{"key":"2_CR29","doi-asserted-by":"crossref","unstructured":"Wu, Q., Wang, H., Gu, Q., Wang, H.: Contextual bandits in a collaborative environment. In: Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 529\u2013538. ACM (2016)","DOI":"10.1145\/2911451.2911528"}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","Collaborative Computing: Networking, Applications and Worksharing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-12981-1_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,21]],"date-time":"2019-05-21T01:16:34Z","timestamp":1558401394000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-12981-1_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030129804","9783030129811"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-12981-1_2","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"type":"print","value":"1867-8211"},{"type":"electronic","value":"1867-822X"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"7 February 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CollaborateCom","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Collaborative Computing: Networking, Applications and Worksharing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 December 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 December 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"colcom2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/collaboratecom.eai-conferences.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"http:\/\/confy.eai.eu","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"77","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"33","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"20","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"43% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}