{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T05:14:02Z","timestamp":1743138842142,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":40,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819972531"},{"type":"electronic","value":"9789819972548"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-981-99-7254-8_42","type":"book-chapter","created":{"date-parts":[[2023,10,21]],"date-time":"2023-10-21T05:01:47Z","timestamp":1697864507000},"page":"544-558","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Incorporating Social-Aware User Preference for\u00a0Video Recommendation"],"prefix":"10.1007","author":[{"given":"Xuanji","family":"Xiao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huaqiang","family":"Dai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Dong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuzi","family":"Niu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuzhen","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pei","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,10,21]]},"reference":[{"key":"42_CR1","doi-asserted-by":"crossref","unstructured":"Ben-Shimon, D., Tsikinovsky, A., Friedmann, M., Shapira, B., Rokach, L., Hoerle, J.: RecSys challenge 2015 and the YOOCHOOSE dataset. In: Proceedings of the 9th ACM Conference on Recommender Systems, pp. 357\u2013358 (2015)","DOI":"10.1145\/2792838.2798723"},{"key":"42_CR2","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1016\/j.knosys.2011.07.021","volume":"26","author":"J Bobadilla","year":"2012","unstructured":"Bobadilla, J., Ortega, F., Hernando, A., Bernal, J.: A collaborative filtering approach to mitigate the new user cold start problem. Knowl.-Based Syst. 26, 225\u2013238 (2012)","journal-title":"Knowl.-Based Syst."},{"issue":"3","key":"42_CR3","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1109\/2.33","volume":"21","author":"GA Carpenter","year":"1988","unstructured":"Carpenter, G.A., Grossberg, S.: The ART of adaptive pattern recognition by a self-organizing neural network. Computer 21(3), 77\u201388 (1988)","journal-title":"Computer"},{"key":"42_CR4","unstructured":"Cheng, A., et al.: Layout-aware webpage quality assessment. arXiv preprint arXiv:2301.12152 (2023)"},{"key":"42_CR5","doi-asserted-by":"crossref","unstructured":"Cheng, H.T., et al.: Wide & deep learning for recommender systems. In: Proceedings of the 1st Workshop on Deep Learning for Recommender Systems, pp. 7\u201310 (2016)","DOI":"10.1145\/2988450.2988454"},{"key":"42_CR6","doi-asserted-by":"crossref","unstructured":"Covington, P., Adams, J., Sargin, E.: Deep neural networks for YouTube recommendations. In: Proceedings of the 10th ACM Conference on Recommender Systems, pp. 191\u2013198 (2016)","DOI":"10.1145\/2959100.2959190"},{"key":"42_CR7","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)"},{"key":"42_CR8","doi-asserted-by":"crossref","unstructured":"Dong, Q., et al.: I$$\\hat{~}$$3 retriever: incorporating implicit interaction in pre-trained language models for passage retrieval. arXiv preprint arXiv:2306.02371 (2023)","DOI":"10.1145\/3477495.3531997"},{"key":"42_CR9","doi-asserted-by":"crossref","unstructured":"Dong, Q., et al.: Incorporating explicit knowledge in pre-trained language models for passage re-ranking. arXiv preprint arXiv:2204.11673 (2022)","DOI":"10.1145\/3477495.3531997"},{"key":"42_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1007\/978-3-030-73197-7_6","volume-title":"Database Systems for Advanced Applications","author":"Q Dong","year":"2021","unstructured":"Dong, Q., Niu, S.: Latent graph recurrent network for document ranking. In: Jensen, C.S., et al. (eds.) DASFAA 2021. LNCS, vol. 12682, pp. 88\u2013103. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-73197-7_6"},{"key":"42_CR11","doi-asserted-by":"crossref","unstructured":"Dong, Q., Niu, S.: Legal judgment prediction via relational learning. In: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 983\u2013992 (2021)","DOI":"10.1145\/3404835.3462931"},{"issue":"1","key":"42_CR12","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1007\/s41019-022-00179-3","volume":"7","author":"Q Dong","year":"2022","unstructured":"Dong, Q., Niu, S., Yuan, T., Li, Y.: Disentangled graph recurrent network for document ranking. Data Sci. Eng. 7(1), 30\u201343 (2022). https:\/\/doi.org\/10.1007\/s41019-022-00179-3","journal-title":"Data Sci. Eng."},{"key":"42_CR13","doi-asserted-by":"crossref","unstructured":"Gope, J., Jain, S.K.: A survey on solving cold start problem in recommender systems. In: 2017 International Conference on Computing, Communication and Automation (ICCCA), pp. 133\u2013138. IEEE (2017)","DOI":"10.1109\/CCAA.2017.8229786"},{"key":"42_CR14","doi-asserted-by":"crossref","unstructured":"Guo, H., Tang, R., Ye, Y., Li, Z., He, X.: DeepFM: a factorization-machine based neural network for CTR prediction. arXiv preprint arXiv:1703.04247 (2017)","DOI":"10.24963\/ijcai.2017\/239"},{"issue":"4","key":"42_CR15","first-page":"1","volume":"5","author":"FM Harper","year":"2015","unstructured":"Harper, F.M., Konstan, J.A.: The movielens datasets: history and context. ACM Trans. Interact. Intell. Syst. (TIIS) 5(4), 1\u201319 (2015)","journal-title":"ACM Trans. Interact. Intell. Syst. (TIIS)"},{"key":"42_CR16","doi-asserted-by":"crossref","unstructured":"Huang, C., et al.: Knowledge-aware coupled graph neural network for social recommendation. In: 35th AAAI Conference on Artificial Intelligence (AAAI) (2021)","DOI":"10.1609\/aaai.v35i5.16533"},{"issue":"9","key":"42_CR17","doi-asserted-by":"publisher","first-page":"5902","DOI":"10.1002\/int.22819","volume":"37","author":"Z Huang","year":"2022","unstructured":"Huang, Z., Lin, Z., Gong, Z., Chen, Y., Tang, Y.: A two-phase knowledge distillation model for graph convolutional network-based recommendation. Int. J. Intell. Syst. 37(9), 5902\u20135923 (2022)","journal-title":"Int. J. Intell. Syst."},{"key":"42_CR18","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"issue":"1","key":"42_CR19","doi-asserted-by":"publisher","first-page":"1568","DOI":"10.4249\/scholarpedia.1568","volume":"2","author":"T Kohonen","year":"2007","unstructured":"Kohonen, T., Honkela, T.: Kohonen network. Scholarpedia 2(1), 1568 (2007)","journal-title":"Scholarpedia"},{"issue":"3","key":"42_CR20","first-page":"553","volume":"68","author":"D Li","year":"2017","unstructured":"Li, D., et al.: User-level microblogging recommendation incorporating social influence. J. Am. Soc. Inf. Sci. 68(3), 553\u2013568 (2017)","journal-title":"J. Am. Soc. Inf. Sci."},{"key":"42_CR21","doi-asserted-by":"crossref","unstructured":"Li, H., et al.: SAILER: structure-aware pre-trained language model for legal case retrieval. arXiv preprint arXiv:2304.11370 (2023)","DOI":"10.1145\/3539618.3591761"},{"key":"42_CR22","doi-asserted-by":"crossref","unstructured":"Lian, J., Zhou, X., Zhang, F., Chen, Z., Xie, X., Sun, G.: xDeepFM: combining explicit and implicit feature interactions for recommender systems. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 1754\u20131763 (2018)","DOI":"10.1145\/3219819.3220023"},{"key":"42_CR23","doi-asserted-by":"crossref","unstructured":"Lu, Y., Fang, Y., Shi, C.: Meta-learning on heterogeneous information networks for cold-start recommendation. In: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 1563\u20131573 (2020)","DOI":"10.1145\/3394486.3403207"},{"key":"42_CR24","unstructured":"Meyffret, S., Guillot, E., M\u00e9dini, L., Laforest, F.: RED: a rich epinions dataset for recommender systems. Ph.D. thesis, LIRIS (2012)"},{"key":"42_CR25","doi-asserted-by":"crossref","unstructured":"Ni, J., Li, J., McAuley, J.: Justifying recommendations using distantly-labeled reviews and fine-grained aspects. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pp. 188\u2013197 (2019)","DOI":"10.18653\/v1\/D19-1018"},{"key":"42_CR26","doi-asserted-by":"crossref","unstructured":"Qin, J., Zhang, W., Wu, X., Jin, J., Fang, Y., Yu, Y.: User behavior retrieval for click-through rate prediction. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 2347\u20132356 (2020)","DOI":"10.1145\/3397271.3401440"},{"key":"42_CR27","doi-asserted-by":"crossref","unstructured":"Seiffert, U.: Self-organizing neural networks: recent advances and applications (2001)","DOI":"10.1007\/978-3-7908-1810-9"},{"key":"42_CR28","series-title":"Lecture Notes on Data Engineering and Communications Technologies","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1007\/978-981-15-9509-7_19","volume-title":"Intelligent Data Communication Technologies and Internet of Things","author":"R Sethi","year":"2021","unstructured":"Sethi, R., Mehrotra, M.: Cold start in recommender systems-a survey from domain perspective. In: Hemanth, J., Bestak, R., Chen, J.I.Z. (eds.) Intelligent Data Communication Technologies and Internet of Things. LNDECT, vol. 57, pp. 223\u2013232. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-981-15-9509-7_19"},{"key":"42_CR29","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1016\/j.aiopen.2021.06.004","volume":"2","author":"Y Su","year":"2021","unstructured":"Su, Y., et al.: CokeBERT: contextual knowledge selection and embedding towards enhanced pre-trained language models. AI Open 2, 127\u2013134 (2021)","journal-title":"AI Open"},{"key":"42_CR30","unstructured":"Sun, Y., et al.: ERNIE: enhanced representation through knowledge integration. arXiv preprint arXiv:1904.09223 (2019)"},{"key":"42_CR31","doi-asserted-by":"crossref","unstructured":"Wan, M., McAuley, J.: Modeling ambiguity, subjectivity, and diverging viewpoints in opinion question answering systems. In: 2016 IEEE 16th International Conference on Data Mining (ICDM), pp. 489\u2013498. IEEE (2016)","DOI":"10.1109\/ICDM.2016.0060"},{"key":"42_CR32","doi-asserted-by":"crossref","unstructured":"Xia, L., et al.: Knowledge-enhanced hierarchical graph transformer network for multi-behavior recommendation (2021)","DOI":"10.1609\/aaai.v35i5.16576"},{"issue":"6","key":"42_CR33","first-page":"6099","volume":"35","author":"L Xia","year":"2022","unstructured":"Xia, L., Huang, C., Xu, Y., Pei, J.: Multi-behavior sequential recommendation with temporal graph transformer. IEEE Trans. Knowl. Data Eng. 35(6), 6099\u20136112 (2022)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"42_CR34","doi-asserted-by":"crossref","unstructured":"Xia, L., Xu, Y., Huang, C., Dai, P., Bo, L.: Graph meta network for multi-behavior recommendation. In: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 757\u2013766 (2021)","DOI":"10.1145\/3404835.3462972"},{"key":"42_CR35","doi-asserted-by":"crossref","unstructured":"Xie, X., et al.: T2Ranking: a large-scale Chinese benchmark for passage ranking. arXiv preprint arXiv:2304.03679 (2023)","DOI":"10.1145\/3539618.3591874"},{"key":"42_CR36","doi-asserted-by":"crossref","unstructured":"Yang, C., Pan, J., Gao, X., Jiang, T., Liu, D., Chen, G.: Cross-task knowledge distillation in multi-task recommendation. arXiv preprint arXiv:2202.09852 (2022)","DOI":"10.1609\/aaai.v36i4.20352"},{"key":"42_CR37","doi-asserted-by":"crossref","unstructured":"Yang, Y., Huang, C., Xia, L., Li, C.: Knowledge graph contrastive learning for recommendation. arXiv preprint arXiv:2205.00976 (2022)","DOI":"10.1145\/3477495.3532009"},{"key":"42_CR38","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"394","DOI":"10.1007\/978-3-030-16145-3_31","volume-title":"Advances in Knowledge Discovery and Data Mining","author":"C Zhang","year":"2019","unstructured":"Zhang, C., Wang, H., Yang, S., Gao, Y.: A contextual bandit approach to personalized online recommendation via sparse interactions. In: Yang, Q., Zhou, Z.-H., Gong, Z., Zhang, M.-L., Huang, S.-J. (eds.) PAKDD 2019. LNCS (LNAI), vol. 11440, pp. 394\u2013406. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-16145-3_31"},{"key":"42_CR39","doi-asserted-by":"crossref","unstructured":"Zhou, G., et al.: Deep interest evolution network for click-through rate prediction. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, pp. 5941\u20135948 (2019)","DOI":"10.1609\/aaai.v33i01.33015941"},{"key":"42_CR40","doi-asserted-by":"crossref","unstructured":"Zhou, G., et al.: Deep interest network for click-through rate prediction. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 1059\u20131068 (2018)","DOI":"10.1145\/3219819.3219823"}],"container-title":["Lecture Notes in Computer Science","Web Information Systems Engineering \u2013 WISE 2023"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-7254-8_42","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,21]],"date-time":"2023-10-21T05:09:29Z","timestamp":1697864969000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-7254-8_42"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9789819972531","9789819972548"],"references-count":40,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-7254-8_42","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"21 October 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"WISE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Web Information Systems Engineering","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Melbourne, VIC","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 October 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 October 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"wise2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.wise-conferences.org\/2023\/","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":"137","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":"33","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":"40","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":"24% - 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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}