{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T21:02:26Z","timestamp":1780088546244,"version":"3.54.0"},"publisher-location":"New York, NY, USA","reference-count":39,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Fund of Joint Laboratory of HUST and Pingan Property & Casualty Research (HPL)"},{"DOI":"10.13039\/501100006374","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62276110, 62172039"],"award-info":[{"award-number":["62276110, 62172039"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,5,13]]},"DOI":"10.1145\/3589335.3648296","type":"proceedings-article","created":{"date-parts":[[2024,5,12]],"date-time":"2024-05-12T18:41:21Z","timestamp":1715539281000},"page":"1-9","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":23,"title":["Knowledge Enhanced Multi-intent Transformer Network for Recommendation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4600-7147","authenticated-orcid":false,"given":"Ding","family":"Zou","sequence":"first","affiliation":[{"name":"CCIIP Lab, School of Computer Science and Technology, Huazhong University of Science and Technology & Taotian Group, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4488-0102","authenticated-orcid":false,"given":"Wei","family":"Wei","sequence":"additional","affiliation":[{"name":"CCIIP Lab, School of Computer Science and Technology, Huazhong University of Science and Techonology & Joint Laboratory of HUST and Pingan Property & Casualty Research (HPL), Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6077-4356","authenticated-orcid":false,"given":"Feida","family":"Zhu","sequence":"additional","affiliation":[{"name":"Singapore Management University, Singapore, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-4454-4846","authenticated-orcid":false,"given":"Chuanyu","family":"Xu","sequence":"additional","affiliation":[{"name":"Taotian Group, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-8302-1170","authenticated-orcid":false,"given":"Tao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Taotian Group, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-0459-4723","authenticated-orcid":false,"given":"Chengfu","family":"Huo","sequence":"additional","affiliation":[{"name":"Taotian Group, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,5,13]]},"reference":[{"key":"e_1_3_2_2_1_1","unstructured":"Antoine Bordes Nicolas Usunier Alberto Garcia-Duran Jason Weston and Oksana Yakhnenko. 2013. Translating embeddings for modeling multi-relational data. In Neural Information Processing Systems (NIPS). 1--9."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"crossref","unstructured":"Yixin Cao Xiang Wang Xiangnan He Zikun Hu and Tat-Seng Chua. 2019. Unifying knowledge graph learning and recommendation: Towards a better understanding of user preferences. In WWW. 151--161.","DOI":"10.1145\/3308558.3313705"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"crossref","unstructured":"Yankai Chen Yaming Yang Yujing Wang Jing Bai Xiangchen Song and Irwin King. 2022. Attentive Knowledge-aware Graph Convolutional Networks with Collaborative Guidance for Personalized Recommendation. In ICDE. 299--311.","DOI":"10.1109\/ICDE53745.2022.00027"},{"key":"e_1_3_2_2_4_1","unstructured":"Xavier Glorot and Yoshua Bengio. 2010. Understanding the difficulty of training deep feedforward neural networks. In AISTATS. 249--256."},{"key":"e_1_3_2_2_5_1","unstructured":"William L Hamilton Rex Ying and Jure Leskovec. 2017. Inductive representation learning on large graphs. In NeurIPS. 1025--1035."},{"key":"e_1_3_2_2_6_1","volume-title":"Wayne Xin Zhao, and Philip S Yu","author":"Hu Binbin","year":"2018","unstructured":"Binbin Hu, Chuan Shi, Wayne Xin Zhao, and Philip S Yu. 2018. Leveraging meta-path based context for top-n recommendation with a neural co-attention model. In SIGKDD. 1531--1540."},{"key":"e_1_3_2_2_7_1","volume-title":"Hongjian Dou, Ji-Rong Wen, and Edward Y Chang.","author":"Huang Jin","year":"2018","unstructured":"Jin Huang, Wayne Xin Zhao, Hongjian Dou, Ji-Rong Wen, and Edward Y Chang. 2018. Improving sequential recommendation with knowledge-enhanced memory networks. In SIGIR. 505--514."},{"key":"e_1_3_2_2_8_1","volume-title":"International Conference on Learning Representations (ICLR","author":"Jang Eric","year":"2017","unstructured":"Eric Jang, Shixiang Gu, and Ben Poole. 2017. Categorical reparametrization with gumble-softmax. In International Conference on Learning Representations (ICLR 2017). OpenReview. net."},{"key":"e_1_3_2_2_9_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980","author":"Kingma Diederik P","year":"2014","unstructured":"Diederik P Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)."},{"key":"e_1_3_2_2_10_1","unstructured":"Yankai Lin Zhiyuan Liu Maosong Sun Yang Liu and Xuan Zhu. 2015. Learning entity and relation embeddings for knowledge graph completion. In AAAI."},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5929"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5346"},{"key":"e_1_3_2_2_13_1","volume-title":"International conference on machine learning. PMLR, 4212--4221","author":"Ma Jianxin","year":"2019","unstructured":"Jianxin Ma, Peng Cui, Kun Kuang, Xin Wang, and Wenwu Zhu. 2019. Disentangled graph convolutional networks. In International conference on machine learning. PMLR, 4212--4221."},{"key":"e_1_3_2_2_14_1","volume-title":"Disentangled Contrastive Collaborative Filtering. arXiv preprint arXiv:2305.02759","author":"Ren Xubin","year":"2023","unstructured":"Xubin Ren, Lianghao Xia, Jiashu Zhao, Dawei Yin, and Chao Huang. 2023. Disentangled Contrastive Collaborative Filtering. arXiv preprint arXiv:2305.02759 (2023)."},{"key":"e_1_3_2_2_15_1","volume-title":"BPR: Bayesian personalized ranking from implicit feedback. arXiv","author":"Rendle Steffen","year":"2012","unstructured":"Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2012. BPR: Bayesian personalized ranking from implicit feedback. arXiv (2012)."},{"key":"e_1_3_2_2_16_1","volume-title":"Wayne Xin Zhao, and S Yu Philip","author":"Shi Chuan","year":"2018","unstructured":"Chuan Shi, Binbin Hu, Wayne Xin Zhao, and S Yu Philip. 2018. Heterogeneous information network embedding for recommendation. IEEE Transactions on Knowledge and Data Engineering (2018), 357--370."},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"crossref","unstructured":"Zhu Sun Jie Yang Jie Zhang Alessandro Bozzon Long-Kai Huang and Chi Xu. 2018. Recurrent knowledge graph embedding for effective recommendation. In RecSys. 297--305.","DOI":"10.1145\/3240323.3240361"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271739"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186175"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"crossref","unstructured":"Hongwei Wang Fuzheng Zhang Mengdi Zhang Jure Leskovec Miao Zhao Wenjie Li and Zhongyuan Wang. 2019c. Knowledge-aware graph neural networks with label smoothness regularization for recommender systems. In SIGKDD. 968--977.","DOI":"10.1145\/3292500.3330836"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"crossref","unstructured":"Hongwei Wang Miao Zhao Xing Xie Wenjie Li and Minyi Guo. 2019d. Knowledge graph convolutional networks for recommender systems. In WWW. 3307--3313.","DOI":"10.1145\/3308558.3313417"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330989"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"crossref","unstructured":"Xiang Wang Tinglin Huang Dingxian Wang Yancheng Yuan Zhenguang Liu Xiangnan He and Tat-Seng Chua. 2021. Learning Intents behind Interactions with Knowledge Graph for Recommendation. In WWW. 878--887.","DOI":"10.1145\/3442381.3450133"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401137"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015329"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401141"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109911"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"crossref","unstructured":"Jiancan Wu Xiang Wang Fuli Feng Xiangnan He Liang Chen Jianxun Lian and Xing Xie. 2021. Self-supervised graph learning for recommendation. In SIGIR. 726--735.","DOI":"10.1145\/3404835.3462862"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3532009"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"crossref","unstructured":"Rex Ying Ruining He Kaifeng Chen Pong Eksombatchai William L Hamilton and Jure Leskovec. 2018. Graph convolutional neural networks for web-scale recommender systems. In SIGKDD. 974--983.","DOI":"10.1145\/3219819.3219890"},{"key":"e_1_3_2_2_31_1","volume-title":"Collaborative filtering with entity similarity regularization in heterogeneous information networks. IJCAI HINA","author":"Yu Xiao","year":"2013","unstructured":"Xiao Yu, Xiang Ren, Quanquan Gu, Yizhou Sun, and Jiawei Han. 2013. Collaborative filtering with entity similarity regularization in heterogeneous information networks. IJCAI HINA (2013)."},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"crossref","unstructured":"Xiao Yu Xiang Ren Yizhou Sun Quanquan Gu Bradley Sturt Urvashi Khandelwal Brandon Norick and Jiawei Han. 2014. Personalized entity recommendation: A heterogeneous information network approach. In WSDM. 283--292.","DOI":"10.1145\/2556195.2556259"},{"key":"e_1_3_2_2_33_1","volume-title":"Defu Lian, Xing Xie, and Wei-Ying Ma.","author":"Zhang Fuzheng","year":"2016","unstructured":"Fuzheng Zhang, Nicholas Jing Yuan, Defu Lian, Xing Xie, and Wei-Ying Ma. 2016. Collaborative knowledge base embedding for recommender systems. In SIGKDD. 353--362."},{"key":"e_1_3_2_2_34_1","volume-title":"Learning over knowledge-base embeddings for recommendation. arXiv preprint arXiv:1803.06540","author":"Zhang Yongfeng","year":"2018","unstructured":"Yongfeng Zhang, Qingyao Ai, Xu Chen, and Pengfei Wang. 2018. Learning over knowledge-base embeddings for recommendation. arXiv preprint arXiv:1803.06540 (2018)."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"crossref","unstructured":"Huan Zhao Quanming Yao Jianda Li Yangqiu Song and Dik Lun Lee. 2017. Meta-graph based recommendation fusion over heterogeneous information networks. In SIGKDD. 635--644.","DOI":"10.1145\/3097983.3098063"},{"key":"e_1_3_2_2_36_1","volume-title":"Adversarial graph disentanglement. arXiv preprint arXiv:2103.07295","author":"Zheng Shuai","year":"2021","unstructured":"Shuai Zheng, Zhenfeng Zhu, Zhizhe Liu, Shuiwang Ji, Jian Cheng, and Yao Zhao. 2021. Adversarial graph disentanglement. arXiv preprint arXiv:2103.07295 (2021)."},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3532025"},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557358"},{"key":"e_1_3_2_2_39_1","volume-title":"Towards Hierarchical Intent Disentanglement for Bundle Recommendation","author":"Zou Ding","year":"2023","unstructured":"Ding Zou, Sen Zhao, Wei Wei, Xian-ling Mao, Ruixuan Li, Dangyang Chen, Rui Fang, and Yuanyuan Fu. 2023. Towards Hierarchical Intent Disentanglement for Bundle Recommendation. IEEE Transactions on Knowledge and Data Engineering (2023). io"}],"event":{"name":"WWW '24: The ACM Web Conference 2024","location":"Singapore Singapore","acronym":"WWW '24","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Companion Proceedings of the ACM Web Conference 2024"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589335.3648296","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3589335.3648296","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:32:43Z","timestamp":1755822763000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589335.3648296"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,13]]},"references-count":39,"alternative-id":["10.1145\/3589335.3648296","10.1145\/3589335"],"URL":"https:\/\/doi.org\/10.1145\/3589335.3648296","relation":{},"subject":[],"published":{"date-parts":[[2024,5,13]]},"assertion":[{"value":"2024-05-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}