{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,20]],"date-time":"2025-09-20T19:28:37Z","timestamp":1758396517613,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030731991"},{"type":"electronic","value":"9783030732004"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":[[2021]]},"DOI":"10.1007\/978-3-030-73200-4_21","type":"book-chapter","created":{"date-parts":[[2021,4,6]],"date-time":"2021-04-06T18:02:46Z","timestamp":1617732166000},"page":"315-320","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Sirius: Sequential Recommendation with Feature Augmented Graph Neural Networks"],"prefix":"10.1007","author":[{"given":"Xinzhou","family":"Dong","sequence":"first","affiliation":[]},{"given":"Beihong","family":"Jin","sequence":"additional","affiliation":[]},{"given":"Wei","family":"Zhuo","sequence":"additional","affiliation":[]},{"given":"Beibei","family":"Li","sequence":"additional","affiliation":[]},{"given":"Taofeng","family":"Xue","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,4,6]]},"reference":[{"unstructured":"Gilmer, J., Schoenholz, S.S., Riley, P.F., Vinyals, O., Dahl, G.E.: Neural message passing for quantum chemistry. In: International Conference on Machine Learning, pp. 1263\u20131272. PMLR (2017)","key":"21_CR1"},{"unstructured":"Gupta, P., Garg, D., Malhotra, P., Vig, L., Shroff, G.: Niser: Normalized item and session representations with graph neural networks. arXiv preprint arXiv:1909.04276 (2019)","key":"21_CR2"},{"doi-asserted-by":"crossref","unstructured":"Hidasi, B., Karatzoglou, A.: Recurrent neural networks with top-k gains for session-based recommendations. In: Proceedings of the 27th ACM International Conference on Information and Knowledge Management, pp. 843\u2013852 (2018)","key":"21_CR3","DOI":"10.1145\/3269206.3271761"},{"unstructured":"Hidasi, B., Karatzoglou, A., Baltrunas, L., Tikk, D.: Session-based recommendations with recurrent neural networks. In: 4th International Conference on Learning Representations, ICLR 2016, San Juan, Puerto Rico, May 2\u20134, 2016, Conference Track Proceedings (2016)","key":"21_CR4"},{"doi-asserted-by":"crossref","unstructured":"Hosseinzadeh Aghdam, M., Hariri, N., Mobasher, B., Burke, R.: Adapting recommendations to contextual changes using hierarchical hidden Markov models. In: Proceedings of the 9th ACM Conference on Recommender Systems, pp. 241\u2013244 (2015)","key":"21_CR5","DOI":"10.1145\/2792838.2799684"},{"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)","key":"21_CR6","DOI":"10.1109\/ICDM.2018.00035"},{"doi-asserted-by":"crossref","unstructured":"Li, J., Wang, Y., McAuley, J.: Time interval aware self-attention for sequential recommendation. In: Proceedings of the 13th International Conference on Web Search and Data Mining, pp. 322\u2013330 (2020)","key":"21_CR7","DOI":"10.1145\/3336191.3371786"},{"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)","key":"21_CR8","DOI":"10.1145\/3132847.3132926"},{"doi-asserted-by":"crossref","unstructured":"Li, R., Shen, Y., Zhu, Y.: Next point-of-interest recommendation with temporal and multi-level context attention. In: 2018 IEEE International Conference on Data Mining (ICDM), pp. 1110\u20131115. IEEE (2018)","key":"21_CR9","DOI":"10.1109\/ICDM.2018.00144"},{"unstructured":"Li, Y., Tarlow, D., Brockschmidt, M., Zemel, R.S.: Gated graph sequence neural networks. In: 4th International Conference on Learning Representations, ICLR 2016, San Juan, Puerto Rico, May 2\u20134, 2016, Conference Track Proceedings (2016)","key":"21_CR10"},{"doi-asserted-by":"crossref","unstructured":"Pan, Z., Cai, F., Chen, W., Chen, H., de Rijke, M.: Star graph neural networks for session-based recommendation. In: Proceedings of the 29th ACM International Conference on Information & Knowledge Management, pp. 1195\u20131204 (2020)","key":"21_CR11","DOI":"10.1145\/3340531.3412014"},{"doi-asserted-by":"crossref","unstructured":"Qiu, R., Li, J., Huang, Z., Yin, H.: Rethinking the item order in session-based recommendation with graph neural networks. In: Proceedings of the 28th ACM International Conference on Information and Knowledge Management, pp. 579\u2013588 (2019)","key":"21_CR12","DOI":"10.1145\/3357384.3358010"},{"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)","key":"21_CR13","DOI":"10.1145\/1772690.1772773"},{"unstructured":"Velickovic, P., Cucurull, G., Casanova, A., Romero, A., Li\u00f2, P., Bengio, Y.: Graph attention networks. CoRR (2017)","key":"21_CR14"},{"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)","key":"21_CR15","DOI":"10.1609\/aaai.v33i01.3301346"},{"doi-asserted-by":"crossref","unstructured":"Xu, C., et al.: Graph contextualized self-attention network for session-based recommendation. In: IJCAI, pp. 3940\u20133946 (2019)","key":"21_CR16","DOI":"10.24963\/ijcai.2019\/547"},{"doi-asserted-by":"crossref","unstructured":"Ye, W., Wang, S., Chen, X., Wang, X., Qin, Z., Yin, D.: 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)","key":"21_CR17","DOI":"10.1145\/3397271.3401154"}],"container-title":["Lecture Notes in Computer Science","Database Systems for Advanced Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-73200-4_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,6]],"date-time":"2021-04-06T18:07:19Z","timestamp":1617732439000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-73200-4_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030731991","9783030732004"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-73200-4_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"6 April 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DASFAA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database Systems for Advanced Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Taipei","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Taiwan","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 April 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 April 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dasfaa2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/dm.iis.sinica.edu.tw\/DASFAA2021\/index.html","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":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"490","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":"98","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":"33","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":"20% - 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":"4","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":"7","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)"}},{"value":"Due to the Corona pandemic this event was held virtually.","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)"}}]}}