{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T01:40:46Z","timestamp":1755826846809,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":40,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,5,30]],"date-time":"2024-05-30T00:00:00Z","timestamp":1717027200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100006374","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2023A1515012685?2023A1515011296"],"award-info":[{"award-number":["2023A1515012685?2023A1515011296"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Fund of National Engineering Laboratory for Big Data System Computing Technology","award":["SZU-BDSC-OF2024-14"],"award-info":[{"award-number":["SZU-BDSC-OF2024-14"]}]},{"name":"Open Research Fund from Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ)","award":["GML-KF-22-28"],"award-info":[{"award-number":["GML-KF-22-28"]}]},{"name":"table Support Project of Shenzhen under Grant","award":["20231120145719001"],"award-info":[{"award-number":["20231120145719001"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,5,30]]},"DOI":"10.1145\/3652583.3658030","type":"proceedings-article","created":{"date-parts":[[2024,6,7]],"date-time":"2024-06-07T06:30:40Z","timestamp":1717741840000},"page":"960-968","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Discovering Multi-Relational Integration for Knowledge Tracing with Retentive Networks"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-8884-1714","authenticated-orcid":false,"given":"Zhou","family":"Linhao","sequence":"first","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University &amp; National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7524-5999","authenticated-orcid":false,"given":"Zhong","family":"Shenghua","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9664-821X","authenticated-orcid":false,"given":"Xiao","family":"Zhijiao","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"}]}],"member":"320","published-online":{"date-parts":[[2024,6,7]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331195"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3569576"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2566486.2568042"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/11774303_17"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-69132-7_111"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCECT57938.2023.10140232"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compedu.2004.01.006"},{"volume-title":"Artificial Intelligence in Education, Ig Ibert Bittencourt, Mutlu Cukurova, Kasia Muldner, Rose Luckin, and Eva Mill\u00e1n (Eds.)","author":"Choi Youngduck","key":"e_1_3_2_1_8_1","unstructured":"Youngduck Choi, Youngnam Lee, Dongmin Shin, Junghyun Cho, Seoyon Park, Seewoo Lee, Jineon Baek, Chan Bae, Byungsoo Kim, and Jaewe Heo. 2020. EdNet: A Large-Scale Hierarchical Dataset in Education. In Artificial Intelligence in Education, Ig Ibert Bittencourt, Mutlu Cukurova, Kasia Muldner, Rose Luckin, and Eva Mill\u00e1n (Eds.). Springer International Publishing, Cham, 69--73."},{"key":"e_1_3_2_1_9_1","volume-title":"Knowledge tracing: Modeling the acquisition of procedural knowledge. User modeling and user-adapted interaction","author":"Corbett Albert T","year":"1994","unstructured":"Albert T Corbett and John R Anderson. 1994. Knowledge tracing: Modeling the acquisition of procedural knowledge. User modeling and user-adapted interaction , Vol. 4 (1994), 253--278."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3580595"},{"key":"e_1_3_2_1_11_1","volume-title":"Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)."},{"key":"e_1_3_2_1_12_1","volume-title":"What is a hidden Markov model? Nature biotechnology","author":"Eddy Sean R","year":"2004","unstructured":"Sean R Eddy. 2004. What is a hidden Markov model? Nature biotechnology, Vol. 22, 10 (2004), 1315--1316."},{"volume-title":"Item response theory","author":"Embretson Susan E","key":"e_1_3_2_1_13_1","unstructured":"Susan E Embretson and Steven P Reise. 2013. Item response theory. Psychology Press."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.116670"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.03.014"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2022.11.016"},{"key":"e_1_3_2_1_17_1","volume-title":"Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907","author":"Kipf Thomas N","year":"2016","unstructured":"Thomas N Kipf and Max Welling. 2016. Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)."},{"key":"e_1_3_2_1_18_1","volume-title":"Deep learning. nature","author":"LeCun Yann","year":"2015","unstructured":"Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. Deep learning. nature, Vol. 521, 7553 (2015), 436--444."},{"key":"e_1_3_2_1_19_1","volume-title":"Broader and Deeper: A Multi-Features with Latent Relations BERT Knowledge Tracing Model. In European Conference on Technology Enhanced Learning. Springer, 183--197","author":"Li Zhaoxing","year":"2023","unstructured":"Zhaoxing Li, Mark Jacobsen, Lei Shi, Yunzhan Zhou, and Jindi Wang. 2023. Broader and Deeper: A Multi-Features with Latent Relations BERT Knowledge Tracing Model. In European Conference on Technology Enhanced Learning. Springer, 183--197."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498374"},{"key":"e_1_3_2_1_21_1","first-page":"64","article-title":"Recurrent neural networks","volume":"5","author":"Medsker Larry R","year":"2001","unstructured":"Larry R Medsker and LC Jain. 2001. Recurrent neural networks. Design and Applications, Vol. 5, 64--67 (2001), 2.","journal-title":"Design and Applications"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3350546.3352513"},{"key":"e_1_3_2_1_23_1","volume-title":"A self-attentive model for knowledge tracing. arXiv preprint arXiv:1907.06837","author":"Pandey Shalini","year":"2019","unstructured":"Shalini Pandey and George Karypis. 2019. A self-attentive model for knowledge tracing. arXiv preprint arXiv:1907.06837 (2019)."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411994"},{"key":"e_1_3_2_1_25_1","volume-title":"Practice and forgetting effects on vocabulary memory: An activation-based model of the spacing effect. Cognitive science","author":"Pavlik Philip I","year":"2005","unstructured":"Philip I Pavlik Jr and John R Anderson. 2005. Practice and forgetting effects on vocabulary memory: An activation-based model of the spacing effect. Cognitive science, Vol. 29, 4 (2005), 559--586."},{"key":"e_1_3_2_1_26_1","volume-title":"Performance Factors Analysis--A New Alternative to Knowledge Tracing. Online Submission","author":"Pavlik Philip I","year":"2009","unstructured":"Philip I Pavlik Jr, Hao Cen, and Kenneth R Koedinger. 2009. Performance Factors Analysis--A New Alternative to Knowledge Tracing. Online Submission (2009)."},{"key":"e_1_3_2_1_27_1","volume-title":"Modeling Students' Memory for Application in Adaptive Educational Systems","author":"Pel\u00e1nek Radek","year":"2015","unstructured":"Radek Pel\u00e1nek. 2015. Modeling Students' Memory for Application in Adaptive Educational Systems. International Educational Data Mining Society (2015)."},{"key":"e_1_3_2_1_28_1","volume-title":"Deep knowledge tracing. Advances in neural information processing systems","author":"Piech Chris","year":"2015","unstructured":"Chris Piech, Jonathan Bassen, Jonathan Huang, Surya Ganguli, Mehran Sahami, Leonidas J Guibas, and Jascha Sohl-Dickstein. 2015. Deep knowledge tracing. Advances in neural information processing systems , Vol. 28 (2015)."},{"key":"e_1_3_2_1_29_1","volume-title":"Markus Hagenbuchner, and Gabriele Monfardini.","author":"Scarselli Franco","year":"2008","unstructured":"Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini. 2008. The graph neural network model. IEEE transactions on neural networks, Vol. 20, 1 (2008), 61--80."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.108274"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2021.08.100"},{"key":"e_1_3_2_1_32_1","volume-title":"Retentive Network: A Successor to Transformer for Large Language Models. arxiv: 2307.08621 [cs.CL]","author":"Sun Yutao","year":"2023","unstructured":"Yutao Sun, Li Dong, Shaohan Huang, Shuming Ma, Yuqing Xia, Jilong Xue, Jianyong Wang, and Furu Wei. 2023. Retentive Network: A Successor to Transformer for Large Language Models. arxiv: 2307.08621 [cs.CL]"},{"key":"e_1_3_2_1_33_1","volume-title":"International Conference on Ad Hoc Networks. Springer, 260--278","author":"Tan Weicong","year":"2021","unstructured":"Weicong Tan, Yuan Jin, Ming Liu, and He Zhang. 2021. BiDKT: Deep knowledge tracing with BERT. In International Conference on Ad Hoc Networks. Springer, 260--278."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/TLT.2021.3083180"},{"key":"e_1_3_2_1_35_1","volume-title":"Attention is all you need. Advances in neural information processing systems","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems , Vol. 30 (2017)."},{"key":"e_1_3_2_1_36_1","volume-title":"Graph attention networks. arXiv preprint arXiv:1710.10903","author":"Petar Velivc","year":"2017","unstructured":"Petar Velivc kovi\u0107, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio. 2017. Graph attention networks. arXiv preprint arXiv:1710.10903 (2017)."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01261-8_1"},{"key":"e_1_3_2_1_38_1","volume-title":"GIKT: A Graph-Based Interaction Model for Knowledge Tracing. In Machine Learning and Knowledge Discovery in Databases","author":"Yang Yang","year":"2021","unstructured":"Yang Yang, Jian Shen, Yanru Qu, Yunfei Liu, Kerong Wang, Yaoming Zhu, Weinan Zhang, and Yong Yu. 2021. GIKT: A Graph-Based Interaction Model for Knowledge Tracing. In Machine Learning and Knowledge Discovery in Databases, Frank Hutter, Kristian Kersting, Jefrey Lijffijt, and Isabel Valera (Eds.). Springer International Publishing, Cham, 299--315."},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-39112-5_18"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052580"}],"event":{"name":"ICMR '24: International Conference on Multimedia Retrieval","sponsor":["SIGMM ACM Special Interest Group on Multimedia","SIGSOFT ACM Special Interest Group on Software Engineering"],"location":"Phuket Thailand","acronym":"ICMR '24"},"container-title":["Proceedings of the 2024 International Conference on Multimedia Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3652583.3658030","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3652583.3658030","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T08:51:25Z","timestamp":1755766285000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3652583.3658030"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,30]]},"references-count":40,"alternative-id":["10.1145\/3652583.3658030","10.1145\/3652583"],"URL":"https:\/\/doi.org\/10.1145\/3652583.3658030","relation":{},"subject":[],"published":{"date-parts":[[2024,5,30]]},"assertion":[{"value":"2024-06-07","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}