{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,22]],"date-time":"2025-06-22T15:10:01Z","timestamp":1750605001955,"version":"3.41.0"},"publisher-location":"Singapore","reference-count":24,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819687275","type":"print"},{"value":"9789819687282","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-981-96-8728-2_19","type":"book-chapter","created":{"date-parts":[[2025,6,22]],"date-time":"2025-06-22T14:30:52Z","timestamp":1750602652000},"page":"229-241","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi-preference Sequence Recommendation Transformer"],"prefix":"10.1007","author":[{"given":"Xinyu","family":"Zheng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mingyang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuan","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiawei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinghua","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,6,21]]},"reference":[{"key":"19_CR1","unstructured":"Ashkan, A., Kveton, B., Berkovsky, S., et al.: Optimal greedy diversity for recommendation. In: IJCAI, pp. 1742\u20131748 (2015)"},{"key":"19_CR2","doi-asserted-by":"crossref","unstructured":"Chen, W., Ren, P., Cai, F., et al.: Improving end-to-end sequential recommendations with intent-aware diversification. In: Proceedings of the 29th ACM International Conference on Information and Knowledge Management, pp. 175\u2013184 (2020)","DOI":"10.1145\/3340531.3411897"},{"key":"19_CR3","doi-asserted-by":"crossref","unstructured":"Guo, C., Zhang, M., Fang, J., et al.: Session-based recommendation with hierarchical leaping networks. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1705\u20131708 (2020)","DOI":"10.1145\/3397271.3401217"},{"key":"19_CR4","doi-asserted-by":"crossref","unstructured":"He, K., Fan, H., Wu, Y., et al.: Momentum contrast for unsupervised visual representation learning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9729\u20139738 (2020)","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"19_CR5","unstructured":"Hidasi, B., Karatzoglou, A., Baltrunas, L., et al.: Session-based recommendations with recurrent neural networks. In: arXiv preprint arXiv:1511.06939 (2015)"},{"key":"19_CR6","doi-asserted-by":"crossref","unstructured":"Kang, W.C., McAuley, J.: Self-attentive sequential recommendation. In: 2018 IEEE International Conference on Data Mining (ICDM), pp. 197\u2013206. IEEE (2018)","DOI":"10.1109\/ICDM.2018.00035"},{"key":"19_CR7","doi-asserted-by":"crossref","unstructured":"Li, J., Ren, P., Chen, Z., et al.: Neural attentive session-based recommendation. In: Proceedings of the 2017 ACM Conference on Information and Knowledge Management, pp. 1419\u20131428 (2017)","DOI":"10.1145\/3132847.3132926"},{"key":"19_CR8","doi-asserted-by":"crossref","unstructured":"Lin, J., Pan, W., Ming, Z.: Fissa: fusing item similarity models with self-attention networks for sequential recommendation. In: Proceedings of the 14th ACM Conference on Recommender Systems, pp. 130\u2013139 (2020)","DOI":"10.1145\/3383313.3412247"},{"key":"19_CR9","doi-asserted-by":"crossref","unstructured":"Liu, C., Li, X., Cai, G., et al.: Noninvasive self-attention for side information fusion in sequential recommendation. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 4249\u20134256 (2021)","DOI":"10.1609\/aaai.v35i5.16549"},{"key":"19_CR10","doi-asserted-by":"crossref","unstructured":"Ma, J., Zhou, C., Yang, H., et al.: Disentangled self-supervision in sequential recommenders. In: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 483\u2013491 (2020)","DOI":"10.1145\/3394486.3403091"},{"key":"19_CR11","doi-asserted-by":"crossref","unstructured":"Ma, M., Ren, P., Lin, Y., et al.: $$\\pi $$-net: a parallel information-sharing network for shared-account cross-domain sequential recommendations. In: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 685\u2013694 (2019)","DOI":"10.1145\/3331184.3331200"},{"key":"19_CR12","doi-asserted-by":"crossref","unstructured":"Ren, R., Liu, Z., Li, Y., et al.: Sequential recommendation with self-attentive multi-adversarial network. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 89\u201398 (2020)","DOI":"10.1145\/3397271.3401111"},{"key":"19_CR13","doi-asserted-by":"crossref","unstructured":"Sun, F., Liu, J., Wu, J., et al.: Bert4rec: sequential recommendation with bidirectional encoder representations from transformer. In: Proceedings of the 28th ACM International Conference on Information and Knowledge Management, pp. 1441\u20131450 (2019)","DOI":"10.1145\/3357384.3357895"},{"key":"19_CR14","doi-asserted-by":"crossref","unstructured":"Sun, P., Wu, L., Wang, M.: Attentive recurrent social recommendation. In: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, pp. 185\u2013194 (2018)","DOI":"10.1145\/3209978.3210023"},{"key":"19_CR15","doi-asserted-by":"crossref","unstructured":"Sun, Y., Yuan, F., Yang, M., et al.: A generic network compression framework for sequential recommender systems. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1299\u20131308 (2020)","DOI":"10.1145\/3397271.3401125"},{"key":"19_CR16","doi-asserted-by":"crossref","unstructured":"Tang, J., Wang, K.: Personalized top-n sequential recommendation via convolutional sequence embedding. In: Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, pp. 565\u2013573 (2018)","DOI":"10.1145\/3159652.3159656"},{"key":"19_CR17","doi-asserted-by":"crossref","unstructured":"Wu, J., Cai, R., Wang, H.: D\u00e9j\u00e0 vu: a contextualized temporal attention mechanism for sequential recommendation. In: Proceedings of the Web Conference 2020, pp. 2199\u20132209 (2020)","DOI":"10.1145\/3366423.3380285"},{"key":"19_CR18","unstructured":"Wu, L., Li, S., Hsieh, C.J., et al.: Stochastic shared embeddings: data-driven regularization of embedding layers. In: Advances in Neural Information Processing Systems (2019)"},{"key":"19_CR19","doi-asserted-by":"crossref","unstructured":"Wu, L., Li, S., Hsieh, C.J., et al.: SSE-PT: sequential recommendation via personalized transformer. In: Proceedings of the 14th ACM Conference on Recommender Systems, pp. 328\u2013337 (2020)","DOI":"10.1145\/3383313.3412258"},{"key":"19_CR20","unstructured":"Yao, T., Yi, X., Cheng, D.Z., et al.: Self-supervised learning for deep models in recommendations. arXiv preprint arXiv:2007.12865 (2020)"},{"key":"19_CR21","doi-asserted-by":"crossref","unstructured":"Ye, W., Wang, S., Chen, X., et al.: Time matters: sequential recommendation with complex temporal information. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1459\u20131468 (2020)","DOI":"10.1145\/3397271.3401154"},{"key":"19_CR22","doi-asserted-by":"crossref","unstructured":"Yuan, F., He, X., Karatzoglou, A., et al.: Parameter-efficient transfer from sequential behaviors for user modeling and recommendation. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1469\u20131478 (2020)","DOI":"10.1145\/3397271.3401156"},{"key":"19_CR23","doi-asserted-by":"crossref","unstructured":"Zhou, C., Ma, J., Zhang, J., et al.: Contrastive learning for debiased candidate generation in large-scale recommender systems. In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, pp. 3985\u20133995 (2021)","DOI":"10.1145\/3447548.3467102"},{"key":"19_CR24","doi-asserted-by":"crossref","unstructured":"Zhou, K., Wang, H., Zhao, W.X., et al.: S3-rec: self-supervised learning for sequential recommendation with mutual information maximization. In: Proceedings of the 29th ACM International Conference on Information and Knowledge Management, pp. 1893\u20131902 (2020)","DOI":"10.1145\/3340531.3411954"}],"container-title":["Lecture Notes in Computer Science","Wireless Artificial Intelligent Computing Systems and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-8728-2_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,22]],"date-time":"2025-06-22T14:31:00Z","timestamp":1750602660000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-8728-2_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819687275","9789819687282"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-8728-2_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"21 June 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"WASA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Wireless Artificial Intelligent Computing Systems and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tokyo","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Japan","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 June 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 June 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"wasa2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/wasa-conference.org\/WASA2025\/index.html#","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}