{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T03:21:10Z","timestamp":1740108070835,"version":"3.37.3"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2022,2,5]],"date-time":"2022-02-05T00:00:00Z","timestamp":1644019200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,2,5]],"date-time":"2022-02-05T00:00:00Z","timestamp":1644019200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61702526"],"award-info":[{"award-number":["61702526"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Postgraduate Scientic Research Innovation Project of Hunan Province","award":["CX20200055"],"award-info":[{"award-number":["CX20200055"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2022,6]]},"DOI":"10.1007\/s00521-022-06966-3","type":"journal-article","created":{"date-parts":[[2022,2,5]],"date-time":"2022-02-05T08:13:43Z","timestamp":1644048823000},"page":"9813-9829","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Session-based recommendation with an importance extraction module"],"prefix":"10.1007","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5484-1743","authenticated-orcid":false,"given":"Zhiqiang","family":"Pan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5709-1682","authenticated-orcid":false,"given":"Fei","family":"Cai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wanyu","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Honghui","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,2,5]]},"reference":[{"issue":"6","key":"6966_CR1","doi-asserted-by":"publisher","first-page":"734","DOI":"10.1109\/TKDE.2005.99","volume":"17","author":"G Adomavicius","year":"2005","unstructured":"G. Adomavicius and A. Tuzhilin. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Trans. Knowl. Data Eng., 17(6):734\u2013749, 2005. DOI: https:\/\/doi.org\/10.1109\/TKDE.2005.99","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"6966_CR2","doi-asserted-by":"publisher","unstructured":"Chen W, Cai F, Chen H, de\u00a0Rijke M (2019) A dynamic co-attention network for session-based recommendation. In: Proceedings of the 28th ACM international conference on information and knowledge management, pp 1461\u20131470. ACM. https:\/\/doi.org\/10.1145\/3357384.3357964","DOI":"10.1145\/3357384.3357964"},{"issue":"4","key":"6966_CR3","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1145\/3343117","volume":"37","author":"W Chen","year":"2019","unstructured":"Chen W, Cai F, Chen H, de\u00a0Rijke M (2019) Joint neural collaborative filtering for recommender systems. ACM Trans. Inf. Syst. 37(4):39\u201339. https:\/\/doi.org\/10.1145\/3343117","journal-title":"ACM Trans Inf Syst"},{"key":"6966_CR4","doi-asserted-by":"publisher","first-page":"106020","DOI":"10.1016\/j.knosys.2020.106020","volume":"200","author":"G Du","year":"2020","unstructured":"Du G, Zhang J, Luo Z, Ma F, Ma L, Li S (2020) Joint imbalanced classification and feature selection for hospital readmissions. Knowl. Based Syst. 200:106020. https:\/\/doi.org\/10.1016\/j.knosys.2020.106020","journal-title":"Knowl Based Syst"},{"key":"6966_CR5","doi-asserted-by":"publisher","unstructured":"He X, Deng K, Wang X, Li Y, Zhang Y, Wang M (2020) Lightgcn: Simplifying and powering graph convolution network for recommendation. In: Proceedings of the 43rd international ACM SIGIR conference on research and development in Information Retrieval, pp 639\u2013648. ACM. https:\/\/doi.org\/10.1145\/3397271.3401063","DOI":"10.1145\/3397271.3401063"},{"key":"6966_CR6","doi-asserted-by":"publisher","unstructured":"He X, Liao L, Zhang H, Nie L, Hu X, Chua T (2017) Neural collaborative filtering. In: Proceedings of the 26th international conference on world wide web, pp 173\u2013182. ACM. https:\/\/doi.org\/10.1145\/3038912.3052569","DOI":"10.1145\/3038912.3052569"},{"key":"6966_CR7","unstructured":"Hidasi B, Karatzoglou A, Baltrunas L, Tikk D (2016) Session-based recommendations with recurrent neural networks. In: 4th international conference on learning representations. arxiv:1511.06939"},{"key":"6966_CR8","doi-asserted-by":"publisher","unstructured":"Jin R, Chai J\u00a0Y, Si L (2004) An automatic weighting scheme for collaborative filtering. In: Proceedings of the 27th annual international ACM SIGIR conference on research and development in Information Retrieval, pp 337\u2013344. ACM. https:\/\/doi.org\/10.1145\/1008992.1009051","DOI":"10.1145\/1008992.1009051"},{"key":"6966_CR9","doi-asserted-by":"publisher","unstructured":"Kang W, McAuley J\u00a0J (2018) Self-attentive sequential recommendation. In: IEEE international conference on data mining, pp 197\u2013206. IEEE Computer Society . https:\/\/doi.org\/10.1109\/ICDM.2018.00035","DOI":"10.1109\/ICDM.2018.00035"},{"key":"6966_CR10","unstructured":"Kipf T\u00a0N, Welling M (2017) Semi-supervised classification with graph convolutional networks. In: 5th international conference on learning representations. https:\/\/openreview.net\/forum?id=SJU4ayYgl"},{"key":"6966_CR11","doi-asserted-by":"publisher","unstructured":"Koren Y (2008) Factorization meets the neighborhood: a multifaceted collaborative filtering model. In: Proceedings of the 14th ACM SIGKDD international conference on knowledge discovery and data mining, pp 426\u2013434. ACM. https:\/\/doi.org\/10.1145\/1401890.1401944","DOI":"10.1145\/1401890.1401944"},{"issue":"8","key":"6966_CR12","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1109\/MC.2009.263","volume":"42","author":"Y Koren","year":"2009","unstructured":"Y. Koren, R. M. Bell, and C. Volinsky. Matrix factorization techniques for recommender systems. Computer, 42(8), 30\u201337, 2009. DOI: https:\/\/doi.org\/10.1109\/MC.2009.263","journal-title":"Computer"},{"key":"6966_CR13","unstructured":"Lee D\u00a0D, Seung H\u00a0S (2000) Algorithms for non-negative matrix factorization. In: Proceedings of the international conference on neural information processing systems, pp 556\u2013562. MIT Press. https:\/\/proceedings.neurips.cc\/paper\/2000\/hash\/f9d1152547c0bde01830b7e8bd60024c-Abstract.html"},{"issue":"9","key":"6966_CR14","doi-asserted-by":"publisher","first-page":"4455","DOI":"10.1007\/s00521-018-3510-5","volume":"31","author":"H Li","year":"2019","unstructured":"H. Li, H. Li, S. Zhang, Z. Zhong, and J. Cheng. Intelligent learning system based on personalized recommendation technology. Neural Comput. Appl., 31(9):4455\u20134462, 2019. DOI: https:\/\/doi.org\/10.1007\/s00521-018-3510-5","journal-title":"Neural Comput Appl"},{"key":"6966_CR15","doi-asserted-by":"publisher","unstructured":"Li J, Ren P, Chen Z, Ren Z, Lian T, Ma J (2017) Neural attentive session-based recommendation. In: Proceedings of the 2017 ACM on conference on information and knowledge management, pp 1419\u20131428. ACM. https:\/\/doi.org\/10.1145\/3132847.3132926","DOI":"10.1145\/3132847.3132926"},{"issue":"1","key":"6966_CR16","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1109\/MIC.2003.1167344","volume":"7","author":"G Linden","year":"2003","unstructured":"Linden G, Smith B, York J (2003) Amazon.com recommendations: Item-to-item collaborative filtering. IEEE Internet Comput 7(1):76\u201380. https:\/\/doi.org\/10.1109\/MIC.2003.1167344","journal-title":"IEEE Internet Comput"},{"key":"6966_CR17","doi-asserted-by":"publisher","unstructured":"Liu Q, Zeng Y, Mokhosi R, Zhang H (2018) 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. ACM. https:\/\/doi.org\/10.1145\/3219819.3219950","DOI":"10.1145\/3219819.3219950"},{"key":"6966_CR18","doi-asserted-by":"publisher","unstructured":"Meng W, Yang D, Xiao Y (2020) 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. ACM. https:\/\/doi.org\/10.1145\/3397271.3401098","DOI":"10.1145\/3397271.3401098"},{"key":"6966_CR19","doi-asserted-by":"publisher","unstructured":"Pan Z, Cai F, Ling Y, de\u00a0Rijke M (2020) Rethinking item importance in session-based recommendation. In: Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, pp 1837\u20131840. ACM. https:\/\/doi.org\/10.1145\/3397271.3401274","DOI":"10.1145\/3397271.3401274"},{"key":"6966_CR20","doi-asserted-by":"publisher","unstructured":"Qiu R, Li J, Huang Z, Yin H (2019) 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. ACM. https:\/\/doi.org\/10.1145\/3357384.3358010","DOI":"10.1145\/3357384.3358010"},{"issue":"7","key":"6966_CR21","doi-asserted-by":"publisher","first-page":"2141","DOI":"10.1007\/s00521-018-3891-5","volume":"32","author":"L Ravi","year":"2020","unstructured":"L. Ravi, V. Subramaniyaswamy, M. Devarajan, S. Natarajan, and V. Vijayakumar. Enhancing recommendation stability of collaborative filtering recommender system through bio-inspired clustering ensemble method. Neural Comput. Appl., 32(7):2141\u20132164, 2020. DOI: https:\/\/doi.org\/10.1007\/s00521-018-3891-5","journal-title":"Neural Comput Appl"},{"key":"6966_CR22","doi-asserted-by":"publisher","unstructured":"Rendle S, Freudenthaler C, Schmidt-Thieme L (2010) Factorizing personalized markov chains for next-basket recommendation. In: Proceedings of the 19th international conference on world wide web, pp 811\u2013820. ACM. https:\/\/doi.org\/10.1145\/1772690.1772773","DOI":"10.1145\/1772690.1772773"},{"key":"6966_CR23","doi-asserted-by":"publisher","unstructured":"Sarwar B.\u00a0M., Karypis G, Konstan J.\u00a0A., Riedl J (2001) Item-based collaborative filtering recommendation algorithms. In: Proceedings of the tenth international world wide web conference, pp 285\u2013295. ACM. https:\/\/doi.org\/10.1145\/371920.372071","DOI":"10.1145\/371920.372071"},{"key":"6966_CR24","unstructured":"Shani G, Heckerman D, Brafman R\u00a0I (2005) An mdp-based recommender system. J Mach Learn Res 6:1265\u20131295. http:\/\/jmlr.org\/papers\/v6\/shani05a.html"},{"key":"6966_CR25","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez A\u00a0N, Kaiser L, Polosukhin I (2017) Attention is all you need. In: Proceedings of the international conference on neural information processing systems, pp 5998\u20136008. MIT Press. https:\/\/proceedings.neurips.cc\/paper\/2017\/hash\/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html"},{"key":"6966_CR26","unstructured":"Vinyals O, Bengio S, Kudlur M (2016) Order matters: sequence to sequence for sets. In: 4th international conference on learning representations . arxiv:1511.06391"},{"key":"6966_CR27","doi-asserted-by":"publisher","unstructured":"Wang F, Xiang X, Cheng J, Yuille A\u00a0L (2017) Normface: L$${}_{\\text{2}}$$ hypersphere embedding for face verification. In: Proceedings of the 2017 ACM on multimedia conference, pp 1041\u20131049. ACM. https:\/\/doi.org\/10.1145\/3123266.3123359","DOI":"10.1145\/3123266.3123359"},{"key":"6966_CR28","doi-asserted-by":"publisher","unstructured":"Wang M, Ren P, Mei L, Chen Z, Ma J, de\u00a0Rijke M (2019) A collaborative session-based recommendation approach with parallel memory modules. In: Proceedings of the 42nd international ACM SIGIR conference on research and development in information retrieval, pp 345\u2013354. ACM. https:\/\/doi.org\/10.1145\/3331184.3331210","DOI":"10.1145\/3331184.3331210"},{"key":"6966_CR29","doi-asserted-by":"publisher","unstructured":"Wang X, He X, Wang M, Feng F, Chua T (2019) Neural graph collaborative filtering. In: Proceedings of the 42nd international ACM SIGIR conference on research and development in information retrieval, pp 165\u2013174. ACM. https:\/\/doi.org\/10.1145\/3331184.3331267","DOI":"10.1145\/3331184.3331267"},{"key":"6966_CR30","doi-asserted-by":"publisher","unstructured":"Wang Z, Wei W, Cong G, Li X, Mao X, Qiu M (2020) 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. ACM. https:\/\/doi.org\/10.1145\/3397271.3401142","DOI":"10.1145\/3397271.3401142"},{"key":"6966_CR31","unstructured":"Weston J, Chopra S, Bordes A (2015) Memory networks. In: 3rd international conference on learning representations. arxiv:1410.3916"},{"key":"6966_CR32","doi-asserted-by":"publisher","unstructured":"Wu S, Tang Y, Zhu Y, Wang L, Xie X, Tan T (2019) Session-based recommendation with graph neural networks. In: The thirty-third AAAI conference on artificial intelligence, pp 346\u2013353. AAAI Press. https:\/\/doi.org\/10.1609\/aaai.v33i01.3301346","DOI":"10.1609\/aaai.v33i01.3301346"},{"key":"6966_CR33","doi-asserted-by":"publisher","unstructured":"Xu C, Zhao P, Liu Y, Sheng V\u00a0S, Xu J, Zhuang F, Fang J, Zhou X (2019) Graph contextualized self-attention network for session-based recommendation. In: Proceedings of the twenty-eighth international joint conference on artificial intelligence, pp 3940\u20133946. https:\/\/doi.org\/10.24963\/ijcai.2019\/547","DOI":"10.24963\/ijcai.2019\/547"},{"key":"6966_CR34","doi-asserted-by":"publisher","unstructured":"Ying H, Zhuang F, Zhang F, Liu Y, Xu G, Xie X, Xiong H, Wu J (2018) Sequential recommender system based on hierarchical attention networks. In: Proceedings of the twenty-seventh international joint conference on artificial intelligence, pp 3926\u20133932. https:\/\/doi.org\/10.24963\/ijcai.2018\/546","DOI":"10.24963\/ijcai.2018\/546"},{"issue":"1","key":"6966_CR35","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1109\/TII.2015.2475218","volume":"12","author":"H Zhang","year":"2016","unstructured":"H. Zhang, Y. Ji, J. Li, and Y. Ye. A triple wing harmonium model for movie recommendation. IEEE Trans. Ind. Informatics, 12(1), 231\u2013239, 2016. DOI: https:\/\/doi.org\/10.1109\/TII.2015.2475218","journal-title":"IEEE Trans Ind Inf"},{"issue":"10","key":"6966_CR36","doi-asserted-by":"publisher","first-page":"4268","DOI":"10.1109\/TCYB.2019.2900159","volume":"50","author":"H Zhang","year":"2020","unstructured":"H. Zhang, Y. Sun, M. Zhao, T. W. S. Chow, and Q. M. J. Wu. Bridging user interest to item content for recommender systems: An optimization model. IEEE Trans. Cybern., 50(10):4268\u20134280, 2020. DOI: https:\/\/doi.org\/10.1109\/TCYB.2019.2900159","journal-title":"IEEE Trans Cybern"},{"key":"6966_CR37","doi-asserted-by":"publisher","unstructured":"Zhang J, Lin Y, Jiang M, Li S, Tang Y, Tan K\u00a0C (2020) Multi-label feature selection via global relevance and redundancy optimization. In: Proceedings of the twenty-ninth international joint conference on artificial intelligence, pp 2512\u20132518. https:\/\/doi.org\/10.24963\/ijcai.2020\/348","DOI":"10.24963\/ijcai.2020\/348"},{"key":"6966_CR38","unstructured":"Zhang S, Tay Y, Yao L, Sun A (2018) Next item recommendation with self-attention. arXiv preprint arXiv:1808.06414"},{"issue":"1","key":"6966_CR39","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3285029","volume":"52","author":"S Zhang","year":"2019","unstructured":"Zhang S, Yao L, Sun A, Tay Y (2019) Deep learning based recommender system: a survey and new perspectives. ACM Comput Surv 52(1):51\u201353. https:\/\/doi.org\/10.1145\/3285029","journal-title":"ACM Comput Surv"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-022-06966-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-022-06966-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-022-06966-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,16]],"date-time":"2022-05-16T06:10:10Z","timestamp":1652681410000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-022-06966-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,5]]},"references-count":39,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2022,6]]}},"alternative-id":["6966"],"URL":"https:\/\/doi.org\/10.1007\/s00521-022-06966-3","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2022,2,5]]},"assertion":[{"value":"11 January 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 January 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 February 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}