{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T14:24:43Z","timestamp":1760711083566,"version":"3.40.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031208676"},{"type":"electronic","value":"9783031208683"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-20868-3_5","type":"book-chapter","created":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T23:29:12Z","timestamp":1667518152000},"page":"60-73","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Cross-View Contrastive Learning for\u00a0Knowledge-Aware Session-Based Recommendation"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4962-1337","authenticated-orcid":false,"given":"Xiaohui","family":"Zhang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5104-8982","authenticated-orcid":false,"given":"Huifang","family":"Ma","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6378-7272","authenticated-orcid":false,"given":"Fanyi","family":"Yang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5313-6134","authenticated-orcid":false,"given":"Zhixin","family":"Li","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7262-4707","authenticated-orcid":false,"given":"Liang","family":"Chang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,11,4]]},"reference":[{"key":"5_CR1","doi-asserted-by":"crossref","unstructured":"Wu, S., Tang, Y., Zhu, Y., Wang, L., Xie, X., Tan, T.: Session-based recommendation with graph neural networks. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, pp. 346\u2013353 (2019)","DOI":"10.1609\/aaai.v33i01.3301346"},{"issue":"7","key":"5_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3465401","volume":"54","author":"S Wang","year":"2021","unstructured":"Wang, S., Cao, L., Wang, Y., Sheng, Q.Z., Orgun, M.A., Lian, D.: A survey on session-based recommender systems. ACM Comput. Surv. 54(7), 1\u201338 (2021)","journal-title":"ACM Comput. Surv."},{"key":"5_CR3","doi-asserted-by":"crossref","unstructured":"Zhang, X., et al.: Price does matter! modeling price and interest preferences in session-based recommendation. In: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (2022)","DOI":"10.1145\/3477495.3532043"},{"key":"5_CR4","doi-asserted-by":"crossref","unstructured":"Rendle, S., Freudenthaler, C., Schmidt-Thieme, L.: Factorizing personalized markov chains for next-basket recommendation. In: Proceedings of the 19th International Conference on World Wide Web, pp. 811\u2013820 (2010)","DOI":"10.1145\/1772690.1772773"},{"key":"5_CR5","unstructured":"Hidasi, B., Karatzoglou, A., Baltrunas, L., Tikk, D.: Session-based recommendations with recurrent neural networks. In: Proceedings of the 4th International Conference on Learning Representations (2016)"},{"key":"5_CR6","doi-asserted-by":"crossref","unstructured":"Li, J., Ren, P., Chen, Z., Ren, Z., Lian, T., Ma, J.: Neural attentive session-based recommendation. In: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, pp. 1419\u20131428 (2017)","DOI":"10.1145\/3132847.3132926"},{"key":"5_CR7","doi-asserted-by":"crossref","unstructured":"Liu, Q., Zeng, Y., Mokhosi, R., Zhang, H.: Stamp: short-term attention\/memory priority model for session-based recommendation. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 1831\u20131839 (2018)","DOI":"10.1145\/3219819.3219950"},{"issue":"3","key":"5_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3382764","volume":"38","author":"R Qiu","year":"2020","unstructured":"Qiu, R., Huang, Z., Li, J., Yin, H.: Exploiting cross-session information for session-based recommendation with graph neural networks. ACM Trans. Inf. Syst. (TOIS) 38(3), 1\u201323 (2020)","journal-title":"ACM Trans. Inf. Syst. (TOIS)"},{"key":"5_CR9","doi-asserted-by":"publisher","first-page":"7614","DOI":"10.1002\/int.22896","volume":"37","author":"X Zhang","year":"2022","unstructured":"Zhang, X., Ma, H., Gao, Z., Li, Z., Chang, L.: Exploiting cross-session information for knowledge-aware session-based recommendation via graph attention networks. Int. J. Intell. Syst. 37, 7614\u20137637 (2022)","journal-title":"Int. J. Intell. Syst."},{"key":"5_CR10","doi-asserted-by":"crossref","unstructured":"Meng, W., Yang, D., Xiao, Y.: Incorporating user micro-behaviors and item knowledge into multi-task learning for session-based recommendation. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1091\u20131100 (2020)","DOI":"10.1145\/3397271.3401098"},{"key":"5_CR11","doi-asserted-by":"crossref","unstructured":"Yuan, J., Song, Z., Sun, M., Wang, X., Zhao, W.X.: Dual sparse attention network for session-based recommendation. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, pp. 4635\u20134643 (2021)","DOI":"10.1609\/aaai.v35i5.16593"},{"key":"5_CR12","doi-asserted-by":"publisher","unstructured":"Zhang, X., Ma, H., Gao, Z., Li, Z., Chang, L.: Enhancing session-based recommendation with global context information and knowledge graph. In: International Conference on Database Systems for Advanced Applications, pp. 281\u2013288. Springer (2022). https:\/\/doi.org\/10.1007\/978-3-031-00126-0_20","DOI":"10.1007\/978-3-031-00126-0_20"},{"key":"5_CR13","doi-asserted-by":"crossref","unstructured":"Yuan, J., Ji, W., Zhang, D., Pan, J., Wang, X.: Micro-behavior encoding for session-based recommendation. In: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (2022)","DOI":"10.1109\/ICDE53745.2022.00261"},{"key":"5_CR14","first-page":"4","volume":"2","author":"P Velickovic","year":"2019","unstructured":"Velickovic, P., Fedus, W., Hamilton, W.L., Li\u00f2, P., Bengio, Y., Hjelm, R.D.: Deep graph infomax. 2, 4 (2019)","journal-title":"Deep graph infomax."},{"key":"5_CR15","first-page":"1","volume":"33","author":"X Liu","year":"2021","unstructured":"Liu, X., et al.: Self-supervised learning: Generative or contrastive. IEEE Trans. Knowl. Data Eng. 33, 1\u201324 (2021)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"5_CR16","unstructured":"Xu, D., Cheng, W., Luo, D., Chen, H., Zhang, X.: InfoGCL: information-aware graph contrastive learning. In: Advances in Neural Information Processing Systems, vol. 34 (2021)"},{"key":"5_CR17","doi-asserted-by":"crossref","unstructured":"Zou, D., et al.: Multi-level cross-view contrastive learning for knowledge-aware recommender system. In: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (2022)","DOI":"10.1145\/3477495.3532025"},{"key":"5_CR18","doi-asserted-by":"crossref","unstructured":"Xia, X., Yin, H., Yu, J., Wang, Q., Cui, L., Zhang, X.: Self-supervised hypergraph convolutional networks for session-based recommendation. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, pp. 4503\u20134511 (2021)","DOI":"10.1609\/aaai.v35i5.16578"},{"key":"5_CR19","doi-asserted-by":"crossref","unstructured":"Xia, X., Yin, H., Yu, J., Shao, Y., Cui, L.: Self-supervised graph co-training for session-based recommendation. In: Proceedings of the 30th ACM International Conference on Information & Knowledge Management, pp. 2180\u20132190 (2021)","DOI":"10.1145\/3459637.3482388"},{"key":"5_CR20","doi-asserted-by":"crossref","unstructured":"Wang, Z., Wei, W., Cong, G., Li, X.L., Mao, X.L., Qiu, M.: Global context enhanced graph neural networks for session-based recommendation. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 169\u2013178 (2020)","DOI":"10.1145\/3397271.3401142"},{"key":"5_CR21","doi-asserted-by":"crossref","unstructured":"Huang, C., et al.: Graph-enhanced multi-task learning of multi-level transition dynamics for session-based recommendation. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, pp. 4123\u20134130 (2021)","DOI":"10.1609\/aaai.v35i5.16534"},{"key":"5_CR22","unstructured":"Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. In: Proceedings of the 3rd International Conference on Learning Representations (2014)"},{"key":"5_CR23","doi-asserted-by":"crossref","unstructured":"Feng, Y., You, H., Zhang, Z., Ji, R., Gao, Y.: Hypergraph neural networks. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, pp. 3558\u20133565 (2019)","DOI":"10.1609\/aaai.v33i01.33013558"},{"key":"5_CR24","unstructured":"Wu, F., Souza, A., Zhang, T., Fifty, C., Yu, T., Weinberger, K.: Simplifying graph convolutional networks. In: International Conference on Machine Learning. PMLR, pp. 6861\u20136871 (2019)"},{"key":"5_CR25","unstructured":"Van den Oord, A., Li, Y., Vinyals, O.: Representation learning with contrastive predictive coding. arXiv e-prints (2018)"},{"key":"5_CR26","doi-asserted-by":"crossref","unstructured":"Hou, Y., Hu, B., Zhang, Z., Zhao, W.X.: Core: simple and effective session-based recommendation within consistent representation space. In: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (2022)","DOI":"10.1145\/3477495.3531955"}],"container-title":["Lecture Notes in Computer Science","PRICAI 2022: Trends in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-20868-3_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T23:37:25Z","timestamp":1667518645000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-20868-3_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031208676","9783031208683"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-20868-3_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"4 November 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRICAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific Rim International Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shangai","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":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 November 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 November 2022","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":"pricai2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/pricai.org\/2022\/","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":"432","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":"91","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":"39","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":"21% - 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":"7-8","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":"n\/a","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)"}}]}}