{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T10:21:06Z","timestamp":1743157266594,"version":"3.40.3"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030602581"},{"type":"electronic","value":"9783030602598"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","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":[[2020]]},"DOI":"10.1007\/978-3-030-60259-8_35","type":"book-chapter","created":{"date-parts":[[2020,10,15]],"date-time":"2020-10-15T10:04:33Z","timestamp":1602756273000},"page":"478-492","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["FHAN: Feature-Level Hierarchical Attention Network for Group Event Recommendation"],"prefix":"10.1007","author":[{"given":"Guoqiong","family":"Liao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaobin","family":"Deng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaomei","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changxuan","family":"Wan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,10,16]]},"reference":[{"key":"35_CR1","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1016\/j.ins.2011.11.037","volume":"189","author":"I Garcia","year":"2012","unstructured":"Garcia, I., Pajares, S., Sebastia, L., et al.: Preference elicitation techniques for group recommender systems. Inf. Sci. 189, 155\u2013175 (2012)","journal-title":"Inf. Sci."},{"key":"35_CR2","doi-asserted-by":"crossref","unstructured":"Baltrunas, L., Makcinskas, T., Ricci, F.: Group recommendations with rank aggregation and collaborative filtering. In: RecSys, pp. 119\u2013126 (2010)","DOI":"10.1145\/1864708.1864733"},{"key":"35_CR3","doi-asserted-by":"crossref","unstructured":"Berkovsky, S., Freyne, J.: Group-based recipe recommendations: analysis of data aggregation strategies. In: RecSys, pp. 111\u2013118 (2010)","DOI":"10.1145\/1864708.1864732"},{"key":"35_CR4","doi-asserted-by":"crossref","unstructured":"Yuan, Q., Cong, G., Lin, C.Y.: COM: a generative model for group recommendation. In: SIGKDD, pp. 163\u2013172 (2014)","DOI":"10.1145\/2623330.2623616"},{"issue":"3","key":"35_CR5","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1007\/s11257-008-9061-1","volume":"19","author":"LM De Campos","year":"2009","unstructured":"De Campos, L.M., Fern\u00e1ndez-Luna, J.M., Huete, J.F., et al.: Managing uncertainty in group recommending processes. User Model. User-Adap. Interact. 19(3), 207\u2013242 (2009). https:\/\/doi.org\/10.1007\/s11257-008-9061-1","journal-title":"User Model. User-Adap. Interact."},{"key":"35_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"596","DOI":"10.1007\/978-3-540-72079-9_20","volume-title":"The Adaptive Web","author":"A Jameson","year":"2007","unstructured":"Jameson, A., Smyth, B.: Recommendation to groups. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web. LNCS, vol. 4321, pp. 596\u2013627. Springer, Heidelberg (2007). https:\/\/doi.org\/10.1007\/978-3-540-72079-9_20"},{"key":"35_CR7","doi-asserted-by":"publisher","first-page":"677","DOI":"10.1007\/978-0-387-85820-3_21","volume-title":"Recommender Systems Handbook","author":"J Masthoff","year":"2011","unstructured":"Masthoff, J.: Group recommender systems: combining individual models. In: Ricci, F., Rokach, L., Shapira, B., Kantor, P.B. (eds.) Recommender Systems Handbook, pp. 677\u2013702. Springer, Boston, MA (2011). https:\/\/doi.org\/10.1007\/978-0-387-85820-3_21"},{"issue":"1","key":"35_CR8","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1007\/s11257-006-9005-6","volume":"16","author":"Z Yu","year":"2006","unstructured":"Yu, Z., Zhou, X., Hao, Y., et al.: TV program recommendation for multiple viewers based on user profile merging. User Model. User-Adap. Interact. 16(1), 63\u201382 (2006). https:\/\/doi.org\/10.1007\/s11257-006-9005-6","journal-title":"User Model. User-Adap. Interact."},{"key":"35_CR9","doi-asserted-by":"crossref","unstructured":"Seko, S., Yagi, T., Motegi, M., et al.: Group recommendation using feature space representing behavioral tendency and power balance among members. In: RecSys, pp. 101\u2013108 (2011)","DOI":"10.1145\/2043932.2043953"},{"issue":"3","key":"35_CR10","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.ins.2014.08.072","volume":"294","author":"VR Kagita","year":"2015","unstructured":"Kagita, V.R., Pujari, A.K., Padmanabhan, V.: Virtual user approach for group recommender systems using precedence relations. Inf. Sci. 294(3), 15\u201330 (2015)","journal-title":"Inf. Sci."},{"issue":"3","key":"35_CR11","doi-asserted-by":"publisher","first-page":"2082","DOI":"10.1016\/j.eswa.2007.02.008","volume":"34","author":"YL Chen","year":"2008","unstructured":"Chen, Y.L., Cheng, L.C., Chuang, C.N.: A group recommendation system with consideration of interactions among group members. Expert Syst. Appl. 34(3), 2082\u20132090 (2008)","journal-title":"Expert Syst. Appl."},{"key":"35_CR12","doi-asserted-by":"crossref","unstructured":"Naamani-Dery, L., Kalech, M., Rokach, L., et al.: Preference elicitation for narrowing the recommended list for groups. In: RecSys, pp. 333\u2013336 (2014)","DOI":"10.1145\/2645710.2645760"},{"issue":"11","key":"35_CR13","doi-asserted-by":"publisher","first-page":"1875","DOI":"10.1109\/TMM.2015.2477044","volume":"17","author":"K Cho","year":"2015","unstructured":"Cho, K., Courville, A., Bengio, Y.: Describing multimedia content using attention-based encoder-decoder networks. IEEE Trans. Multimedia 17(11), 1875\u20131886 (2015)","journal-title":"IEEE Trans. Multimedia"},{"key":"35_CR14","doi-asserted-by":"crossref","unstructured":"Lee, J., Shin, J.H., Kim, J.S.: Interactive visualization and manipulation of attention-based neural machine translation. In: EMNLP, pp. 121\u2013126. ACL (2017)","DOI":"10.18653\/v1\/D17-2021"},{"issue":"12","key":"35_CR15","first-page":"2354","volume":"30","author":"X He","year":"2018","unstructured":"He, X., He, Z., Song, J., et al.: NAIS: neural attentive item similarity model for recommendation. IEEE TKDE 30(12), 2354\u20132366 (2018)","journal-title":"IEEE TKDE"},{"key":"35_CR16","doi-asserted-by":"crossref","unstructured":"Kiela, D., Wang, C., Cho, K.: Dynamic meta-embeddings for improved sentence representations. In: EMNLP, pp. 1466\u20131477 (2018)","DOI":"10.18653\/v1\/D18-1176"},{"key":"35_CR17","doi-asserted-by":"crossref","unstructured":"Li, X., Zhao, B., Lu, X.: MAM-RNN: multi-level attention model based RNN for video captioning. In: IJCAI, pp. 2208\u20132214 (2017)","DOI":"10.24963\/ijcai.2017\/307"},{"key":"35_CR18","doi-asserted-by":"crossref","unstructured":"Chen, J., Zhang, H., He, X., et al.: Attentive collaborative filtering: multimedia recommendation with item- and component-level attention. In: SIGIR, pp. 335\u2013344 (2017)","DOI":"10.1145\/3077136.3080797"},{"key":"35_CR19","doi-asserted-by":"crossref","unstructured":"Ying, H., Zhuang, F., Zhang, F., et al.: Sequential recommender system based on hierarchical attention networks. In: The 27th International Joint Conference on Artificial Intelligence (2018)","DOI":"10.24963\/ijcai.2018\/546"},{"key":"35_CR20","doi-asserted-by":"crossref","unstructured":"Zhou, C., Bai, J., Song, J., et al.: ATRank: an attention-based user behavior modeling framework for recommendation. In: AAAI (2018)","DOI":"10.1609\/aaai.v32i1.11618"},{"key":"35_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.neucom.2019.02.045","volume":"341","author":"J Chen","year":"2019","unstructured":"Chen, J., Wang, C., Shi, Q., et al.: Social recommendation based on users\u2019 attention and prefence. Neurocomputing 341, 1\u20139 (2019)","journal-title":"Neurocomputing"},{"key":"35_CR22","doi-asserted-by":"crossref","unstructured":"He, X., Liao, L., Zhang, H., et al.: Neural collaborative filtering. In: WWW, pp. 173\u2013182 (2017)","DOI":"10.1145\/3038912.3052569"},{"key":"35_CR23","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1007\/0-306-48019-0_11","volume-title":"ECSCW","author":"M O\u2019connor","year":"2001","unstructured":"O\u2019connor, M., Cosley, D., Konstan, J.A., Riedl, J.: PolyLens: a recommender system for groups of users. In: Prinz, W., Jarke, M., Rogers, Y., Schmidt, K., Wulf, V. (eds.) ECSCW, pp. 199\u2013218. Springer, Dordrecht (2001). https:\/\/doi.org\/10.1007\/0-306-48019-0_11"},{"key":"35_CR24","first-page":"745","volume":"4","author":"Z Yujie","year":"2016","unstructured":"Yujie, Z., Yulu, D., Xiangwu, M.: Research on group recommender systems and their applications. Chin. J. Comput. 4, 745\u2013764 (2016)","journal-title":"Chin. J. Comput."},{"key":"35_CR25","unstructured":"Breese, J.S., Heckerman, D., Kadie, C.: Empirical analysis of predictive algorithms for collaborative filtering. In: Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence, Madison, USA, pp. 43\u201352 (1998)"},{"key":"35_CR26","doi-asserted-by":"crossref","unstructured":"Vinh Tran, L., Nguyen Pham, T.A., Tay, Y., et al.: Interact and decide: medley of sub-attention networks for effective group recommendation. In: SIGIR, pp. 255\u2013264 (2019)","DOI":"10.1145\/3331184.3331251"},{"key":"35_CR27","doi-asserted-by":"crossref","unstructured":"Cao, D., He, X., Miao, L., et al.: Attentive group recommendation. In: SIGIR, pp. 645\u2013654 (2018)","DOI":"10.1145\/3209978.3209998"}],"container-title":["Lecture Notes in Computer Science","Web and Big Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-60259-8_35","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,23]],"date-time":"2022-11-23T11:39:09Z","timestamp":1669203549000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-60259-8_35"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030602581","9783030602598"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-60259-8_35","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"16 October 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"APWeb-WAIM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tianjin","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":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 August 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 August 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"apwebwaim2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.tjudb.cn\/apwebwaim2020\/","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":"Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"259","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":"68","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":"37","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":"26% - 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":"4.6","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":"Due to the COVID-19 pandemic the conference was organized as a fully online conference.","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)"}}]}}