{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T21:46:49Z","timestamp":1743112009972,"version":"3.40.3"},"publisher-location":"Cham","reference-count":42,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031560682"},{"type":"electronic","value":"9783031560699"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-56069-9_4","type":"book-chapter","created":{"date-parts":[[2024,3,22]],"date-time":"2024-03-22T08:17:45Z","timestamp":1711095465000},"page":"50-65","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Federated Conversational Recommender Systems"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0980-4323","authenticated-orcid":false,"given":"Allen","family":"Lin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9916-0976","authenticated-orcid":false,"given":"Jianling","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3990-4774","authenticated-orcid":false,"given":"Ziwei","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8350-8528","authenticated-orcid":false,"given":"James","family":"Caverlee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,3,23]]},"reference":[{"key":"4_CR1","unstructured":"Ammad-Ud-Din, M., et al.: Federated collaborative filtering for privacy-preserving personalized recommendation system. arXiv preprint arXiv:1901.09888 (2019)"},{"key":"4_CR2","doi-asserted-by":"crossref","unstructured":"Anelli, V.W., Deldjoo, Y., Di Noia, T., Ferrara, A., Narducci, F.: How to put users in control of their data in federated top-n recommendation with learning to rank. In: Proceedings of the 36th Annual ACM Symposium on Applied Computing, pp. 1359\u20131362 (2021)","DOI":"10.1145\/3412841.3442010"},{"issue":"7","key":"4_CR3","doi-asserted-by":"publisher","first-page":"5827","DOI":"10.1109\/JIOT.2019.2952146","volume":"7","author":"PCM Arachchige","year":"2019","unstructured":"Arachchige, P.C.M., Bertok, P., Khalil, I., Liu, D., Camtepe, S., Atiquzzaman, M.: Local differential privacy for deep learning. IEEE Internet Things J. 7(7), 5827\u20135842 (2019)","journal-title":"IEEE Internet Things J."},{"key":"4_CR4","doi-asserted-by":"crossref","unstructured":"Berlioz, A., Friedman, A., Kaafar, M.A., Boreli, R., Berkovsky, S.: Applying differential privacy to matrix factorization. In: Proceedings of the 9th ACM Conference on Recommender Systems, pp. 107\u2013114 (2015)","DOI":"10.1145\/2792838.2800173"},{"key":"4_CR5","doi-asserted-by":"crossref","unstructured":"Beutel, A., Chi, E.H., Cheng, Z., Pham, H., Anderson, J.: Beyond globally optimal: focused learning for improved recommendations. In: TheWebConf (2017)","DOI":"10.1145\/3038912.3052713"},{"issue":"5","key":"4_CR6","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1109\/MIS.2020.3014880","volume":"36","author":"D Chai","year":"2020","unstructured":"Chai, D., Wang, L., Chen, K., Yang, Q.: Secure federated matrix factorization. IEEE Intell. Syst. 36(5), 11\u201320 (2020)","journal-title":"IEEE Intell. Syst."},{"key":"4_CR7","doi-asserted-by":"crossref","unstructured":"Chen, C., Liu, Z., Zhao, P., Zhou, J., Li, X.: Privacy preserving point-of-interest recommendation using decentralized matrix factorization. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 32 (2018)","DOI":"10.1609\/aaai.v32i1.11244"},{"key":"4_CR8","doi-asserted-by":"crossref","unstructured":"Cormode, G., Jha, S., Kulkarni, T., Li, N., Srivastava, D., Wang, T.: Privacy at scale: local differential privacy in practice. In: Proceedings of the 2018 International Conference on Management of Data, pp. 1655\u20131658 (2018)","DOI":"10.1145\/3183713.3197390"},{"key":"4_CR9","doi-asserted-by":"crossref","unstructured":"Deng, Y., Li, Y., Sun, F., Ding, B., Lam, W.: Unified conversational recommendation policy learning via graph-based reinforcement learning. In: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1431\u20131441 (2021)","DOI":"10.1145\/3404835.3462913"},{"key":"4_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/11787006_1","volume-title":"Automata, Languages and Programming","author":"C Dwork","year":"2006","unstructured":"Dwork, C.: Differential privacy. In: Bugliesi, M., Preneel, B., Sassone, V., Wegener, I. (eds.) ICALP 2006. LNCS, vol. 4052, pp. 1\u201312. Springer, Heidelberg (2006). https:\/\/doi.org\/10.1007\/11787006_1"},{"key":"4_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-540-79228-4_1","volume-title":"Theory and Applications of Models of Computation","author":"C Dwork","year":"2008","unstructured":"Dwork, C.: Differential privacy: a survey of results. In: Agrawal, M., Du, D., Duan, Z., Li, A. (eds.) TAMC 2008. LNCS, vol. 4978, pp. 1\u201319. Springer, Heidelberg (2008). https:\/\/doi.org\/10.1007\/978-3-540-79228-4_1"},{"key":"4_CR12","doi-asserted-by":"crossref","unstructured":"Gao, C., Huang, C., Lin, D., Jin, D., Li, Y.: DPLCF: differentially private local collaborative filtering. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 961\u2013970 (2020)","DOI":"10.1145\/3397271.3401053"},{"key":"4_CR13","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1016\/j.aiopen.2021.06.002","volume":"2","author":"C Gao","year":"2021","unstructured":"Gao, C., Lei, W., He, X., de Rijke, M., Chua, T.S.: Advances and challenges in conversational recommender systems: a survey. AI Open 2, 100\u2013126 (2021)","journal-title":"AI Open"},{"key":"4_CR14","doi-asserted-by":"crossref","unstructured":"Gemulla, R., Nijkamp, E., Haas, P.J., Sismanis, Y.: Large-scale matrix factorization with distributed stochastic gradient descent. In: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 69\u201377 (2011)","DOI":"10.1145\/2020408.2020426"},{"key":"4_CR15","doi-asserted-by":"crossref","unstructured":"Graus, M.P., Willemsen, M.C.: Improving the user experience during cold start through choice-based preference elicitation. In: Proceedings of the 9th ACM Conference on Recommender Systems, pp. 273\u2013276 (2015)","DOI":"10.1145\/2792838.2799681"},{"key":"4_CR16","doi-asserted-by":"crossref","unstructured":"Hu, C., Huang, S., Zhang, Y., Liu, Y.: Learning to infer user implicit preference in conversational recommendation. In: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 256\u2013266 (2022)","DOI":"10.1145\/3477495.3531844"},{"key":"4_CR17","doi-asserted-by":"publisher","first-page":"113250","DOI":"10.1016\/j.dss.2020.113250","volume":"131","author":"A Iovine","year":"2020","unstructured":"Iovine, A., Narducci, F., Semeraro, G.: Conversational recommender systems and natural language: a study through the ConveRSE framework. Decis. Support Syst. 131, 113250 (2020)","journal-title":"Decis. Support Syst."},{"issue":"5","key":"4_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3453154","volume":"54","author":"D Jannach","year":"2021","unstructured":"Jannach, D., Manzoor, A., Cai, W., Chen, L.: A survey on conversational recommender systems. ACM Comput. Surv. (CSUR) 54(5), 1\u201336 (2021)","journal-title":"ACM Comput. Surv. (CSUR)"},{"issue":"5","key":"4_CR19","doi-asserted-by":"publisher","first-page":"973","DOI":"10.1287\/opre.2014.1292","volume":"62","author":"H Jiang","year":"2014","unstructured":"Jiang, H., Qi, X., Sun, H.: Choice-based recommender systems: a unified approach to achieving relevancy and diversity. Oper. Res. 62(5), 973\u2013993 (2014)","journal-title":"Oper. Res."},{"key":"4_CR20","unstructured":"Jin, H., Peng, Y., Yang, W., Wang, S., Zhang, Z.: Federated reinforcement learning with environment heterogeneity. In: International Conference on Artificial Intelligence and Statistics, pp. 18\u201337. PMLR (2022)"},{"key":"4_CR21","unstructured":"Kairouz, P., et al.: Advances and open problems in federated learning. Found. Trends\u00ae Mach. Learn. 14(1\u20132), 1\u2013210 (2021)"},{"key":"4_CR22","doi-asserted-by":"crossref","unstructured":"Kalloori, S., Klingler, S.: Horizontal cross-silo federated recommender systems. In: Proceedings of the 15th ACM Conference on Recommender Systems, pp. 680\u2013684 (2021)","DOI":"10.1145\/3460231.3478863"},{"key":"4_CR23","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1007\/11766155_2","volume-title":"Emerging Trends in Information and Communication Security","author":"SKT Lam","year":"2006","unstructured":"Lam, S.K.T., Frankowski, D., Riedl, J.: Do you trust your recommendations? An exploration of security and privacy issues in recommender systems. In: M\u00fcller, G. (ed.) ETRICS 2006. LNCS, vol. 3995, pp. 14\u201329. Springer, Heidelberg (2006). https:\/\/doi.org\/10.1007\/11766155_2"},{"key":"4_CR24","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1007\/978-3-642-24861-0_22","volume-title":"Information Security","author":"J Lee","year":"2011","unstructured":"Lee, J., Clifton, C.: How much is enough? Choosing $$\\varepsilon $$ for differential privacy. In: Lai, X., Zhou, J., Li, H. (eds.) ISC 2011. LNCS, vol. 7001, pp. 325\u2013340. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-24861-0_22"},{"key":"4_CR25","doi-asserted-by":"crossref","unstructured":"Lei, W., et al.: Estimation-action-reflection: towards deep interaction between conversational and recommender systems. In: WSDM (2020)","DOI":"10.1145\/3336191.3371769"},{"key":"4_CR26","doi-asserted-by":"crossref","unstructured":"Lei, W., et al.: Interactive path reasoning on graph for conversational recommendation. In: KDD (2020)","DOI":"10.1145\/3394486.3403258"},{"key":"4_CR27","doi-asserted-by":"crossref","unstructured":"Li, C., Palanisamy, B., Joshi, J.: Differentially private trajectory analysis for points-of-interest recommendation. In: 2017 IEEE International Congress on Big Data (BigData Congress), pp. 49\u201356. IEEE (2017)","DOI":"10.1109\/BigDataCongress.2017.16"},{"key":"4_CR28","doi-asserted-by":"crossref","unstructured":"Lin, A., Wang, J., Zhu, Z., Caverlee, J.: Quantifying and mitigating popularity bias in conversational recommender systems. In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1238\u20131247 (2022)","DOI":"10.1145\/3511808.3557423"},{"key":"4_CR29","doi-asserted-by":"publisher","unstructured":"Massa, P., Avesani, P.: Trust metrics in recommender systems. In: Golbeck, J. (eds.) Computing with Social Trust. Human-Computer Interaction Series. Springer, London (2009). https:\/\/doi.org\/10.1007\/978-1-84800-356-9_10","DOI":"10.1007\/978-1-84800-356-9_10"},{"key":"4_CR30","doi-asserted-by":"crossref","unstructured":"Minto, L., Haller, M., Livshits, B., Haddadi, H.: Stronger privacy for federated collaborative filtering with implicit feedback. In: Proceedings of the 15th ACM Conference on Recommender Systems, pp. 342\u2013350 (2021)","DOI":"10.1145\/3460231.3474262"},{"key":"4_CR31","doi-asserted-by":"crossref","unstructured":"Polat, H., Du, W.: SVD-based collaborative filtering with privacy. In: Proceedings of the 2005 ACM Symposium on Applied Computing, pp. 791\u2013795 (2005)","DOI":"10.1145\/1066677.1066860"},{"key":"4_CR32","doi-asserted-by":"crossref","unstructured":"Qi, T., Wu, F., Wu, C., Huang, Y., Xie, X.: Privacy-preserving news recommendation model learning. arXiv preprint arXiv:2003.09592 (2020)","DOI":"10.18653\/v1\/2020.findings-emnlp.128"},{"key":"4_CR33","doi-asserted-by":"crossref","unstructured":"Rendle, S.: Factorization machines. In: 2010 IEEE International Conference on Data Mining, pp. 995\u20131000 (2010)","DOI":"10.1109\/ICDM.2010.127"},{"key":"4_CR34","doi-asserted-by":"crossref","unstructured":"Riboni, D., Bettini, C.: Private context-aware recommendation of points of interest: an initial investigation. In: 2012 IEEE International Conference on Pervasive Computing and Communications Workshops, pp. 584\u2013589. IEEE (2012)","DOI":"10.1109\/PerComW.2012.6197582"},{"key":"4_CR35","doi-asserted-by":"crossref","unstructured":"Sun, Y., Zhang, Y.: Conversational recommender system. In: SIGIR (2018)","DOI":"10.1145\/3209978.3210002"},{"key":"4_CR36","unstructured":"Sutton, R.S., McAllester, D., Singh, S., Mansour, Y.: Policy gradient methods for reinforcement learning with function approximation. In: Advances in Neural Information Processing Systems, vol. 12 (1999)"},{"key":"4_CR37","doi-asserted-by":"crossref","unstructured":"Van Hasselt, H., Guez, A., Silver, D.: Deep reinforcement learning with double q-learning. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 30 (2016)","DOI":"10.1609\/aaai.v30i1.10295"},{"key":"4_CR38","doi-asserted-by":"crossref","unstructured":"Wu, C., Wu, F., Cao, Y., Huang, Y., Xie, X.: FedGNN: federated graph neural network for privacy-preserving recommendation. arXiv preprint arXiv:2102.04925 (2021)","DOI":"10.1038\/s41467-022-30714-9"},{"key":"4_CR39","doi-asserted-by":"crossref","unstructured":"Xiong, S., Sarwate, A.D., Mandayam, N.B.: Randomized requantization with local differential privacy. In: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2189\u20132193. IEEE (2016)","DOI":"10.1109\/ICASSP.2016.7472065"},{"key":"4_CR40","doi-asserted-by":"crossref","unstructured":"Xu, K., Yang, J., Xu, J., Gao, S., Guo, J., Wen, J.R.: Adapting user preference to online feedback in multi-round conversational recommendation. In: Proceedings of the 14th ACM International Conference on Web Search and Data Mining, pp. 364\u2013372 (2021)","DOI":"10.1145\/3437963.3441791"},{"key":"4_CR41","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1007\/978-3-030-63076-8_16","volume-title":"Federated Learning","author":"L Yang","year":"2020","unstructured":"Yang, L., Tan, B., Zheng, V.W., Chen, K., Yang, Q.: Federated recommendation systems. In: Yang, Q., Fan, L., Yu, H. (eds.) Federated Learning. LNCS (LNAI), vol. 12500, pp. 225\u2013239. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-63076-8_16"},{"issue":"2","key":"4_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3298981","volume":"10","author":"Q Yang","year":"2019","unstructured":"Yang, Q., Liu, Y., Chen, T., Tong, Y.: Federated machine learning: Concept and applications. ACM Trans. Intell. Syst. Technol. (TIST) 10(2), 1\u201319 (2019)","journal-title":"ACM Trans. Intell. Syst. Technol. (TIST)"}],"container-title":["Lecture Notes in Computer Science","Advances in Information Retrieval"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-56069-9_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,22]],"date-time":"2024-03-22T08:19:55Z","timestamp":1711095595000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-56069-9_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031560682","9783031560699"],"references-count":42,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-56069-9_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"23 March 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECIR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Information Retrieval","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Glasgow","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 March 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 March 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecir2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.ecir2024.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"578","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"110","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"69","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"19% - 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 (provided by the conference organizers)"}},{"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 (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"31 (Tracks: Workshop, Tutorial, Industry, Doctoral Consortium)","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}