{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T01:11:34Z","timestamp":1774487494241,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":50,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,8,24]],"date-time":"2024-08-24T00:00:00Z","timestamp":1724457600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,8,25]]},"DOI":"10.1145\/3637528.3671514","type":"proceedings-article","created":{"date-parts":[[2024,8,25]],"date-time":"2024-08-25T04:55:12Z","timestamp":1724561712000},"page":"5307-5316","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Contextual Distillation Model for Diversified Recommendation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-0889-4684","authenticated-orcid":false,"given":"Fan","family":"Li","sequence":"first","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-9540-4080","authenticated-orcid":false,"given":"Xu","family":"Si","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4550-3950","authenticated-orcid":false,"given":"Shisong","family":"Tang","sequence":"additional","affiliation":[{"name":"Kuaishou Inc. & Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9196-2624","authenticated-orcid":false,"given":"Dingmin","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Oxford, Oxford, United Kingdom"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7991-105X","authenticated-orcid":false,"given":"Kunyan","family":"Han","sequence":"additional","affiliation":[{"name":"Kuaishou Inc., Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-2288-6891","authenticated-orcid":false,"given":"Bing","family":"Han","sequence":"additional","affiliation":[{"name":"Kuaishou Inc., Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0277-4638","authenticated-orcid":false,"given":"Guorui","family":"Zhou","sequence":"additional","affiliation":[{"name":"Kuaishou Inc., Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1714-5527","authenticated-orcid":false,"given":"Yang","family":"Song","sequence":"additional","affiliation":[{"name":"Kuaishou Inc., Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7835-9556","authenticated-orcid":false,"given":"Hechang","family":"Chen","sequence":"additional","affiliation":[{"name":"Jilin University, Changchun, China"}]}],"member":"320","published-online":{"date-parts":[[2024,8,24]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403345"},{"key":"e_1_3_2_2_2_1","first-page":"1742","article-title":"Optimal Greedy Diversity for Recommendation","volume":"15","author":"Ashkan Azin","year":"2015","unstructured":"Azin Ashkan, Branislav Kveton, Shlomo Berkovsky, and Zheng Wen. 2015. Optimal Greedy Diversity for Recommendation.. In IJCAI, Vol. 15. 1742--1748.","journal-title":"IJCAI"},{"key":"e_1_3_2_2_3_1","volume-title":"Multimodality Invariant Learning for Multimedia-Based New Item Recommendation. arXiv preprint arXiv:2405.15783","author":"Bai Haoyue","year":"2024","unstructured":"Haoyue Bai, Le Wu, Min Hou, Miaomiao Cai, Zhuangzhuang He, Yuyang Zhou, Richang Hong, and Meng Wang. 2024. Multimodality Invariant Learning for Multimedia-Based New Item Recommendation. arXiv preprint arXiv:2405.15783 (2024)."},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/290941.291025"},{"key":"e_1_3_2_2_5_1","volume-title":"Fast greedy map inference for determinantal point process to improve recommendation diversity. Advances in Neural Information Processing Systems 31","author":"Chen Laming","year":"2018","unstructured":"Laming Chen, Guoxin Zhang, and Eric Zhou. 2018. Fast greedy map inference for determinantal point process to improve recommendation diversity. Advances in Neural Information Processing Systems 31 (2018)."},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052585"},{"key":"e_1_3_2_2_7_1","volume-title":"Contrastive Attention Mechanism for Abstractive Sentence Summarization. arXiv preprint arXiv:1910.13114","author":"Duan Xiangyu","year":"2019","unstructured":"Xiangyu Duan, Hongfei Yu, Mingming Yin, Min Zhang, Weihua Luo, and Yue Zhang. 2019. Contrastive Attention Mechanism for Abstractive Sentence Summarization. arXiv preprint arXiv:1910.13114 (2019)."},{"key":"e_1_3_2_2_8_1","volume-title":"End-to-End Optimization of Quantization-Based Structure Learning and Interventional Next-Item Recommendation. In CAAI International Conference on Artificial Intelligence. 415--429","author":"Fu Kairui","year":"2023","unstructured":"Kairui Fu, Qiaowei Miao, Shengyu Zhang, Kun Kuang, and Fei Wu. 2023. End-to-End Optimization of Quantization-Based Structure Learning and Interventional Next-Item Recommendation. In CAAI International Conference on Artificial Intelligence. 415--429."},{"key":"e_1_3_2_2_9_1","volume-title":"DIET: Customized Slimming for Incompatible Networks in Sequential Recommendation. arXiv:arXiv:2406.08804","author":"Fu Kairui","year":"2024","unstructured":"Kairui Fu, Shengyu Zhang, Zheqi Lv, Jingyuan Chen, and Jiwei Li. 2024. DIET: Customized Slimming for Incompatible Networks in Sequential Recommendation. arXiv:arXiv:2406.08804"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/1864708.1864761"},{"key":"e_1_3_2_2_11_1","volume-title":"Expectation-maximization for learning determinantal point processes. Advances in Neural Information Processing Systems 27","author":"Gillenwater Jennifer A","year":"2014","unstructured":"Jennifer A Gillenwater, Alex Kulesza, Emily Fox, and Ben Taskar. 2014. Expectation-maximization for learning determinantal point processes. Advances in Neural Information Processing Systems 27 (2014)."},{"key":"e_1_3_2_2_12_1","volume-title":"Double Correction Framework for Denoising Recommendation. arXiv preprint arXiv:2405.11272","author":"He Zhuangzhuang","year":"2024","unstructured":"Zhuangzhuang He, Yifan Wang, Yonghui Yang, Peijie Sun, Le Wu, Haoyue Bai, Jinqi Gong, Richang Hong, and Min Zhang. 2024. Double Correction Framework for Denoising Recommendation. arXiv preprint arXiv:2405.11272 (2024)."},{"key":"e_1_3_2_2_13_1","volume-title":"Distilling the Knowledge in a Neural Network. arXiv preprint arXiv:1503.02531","author":"Hinton Geoffrey","year":"2015","unstructured":"Geoffrey Hinton, Oriol Vinyals, and Jeff Dean. 2015. Distilling the Knowledge in a Neural Network. arXiv preprint arXiv:1503.02531 (2015). https:\/\/arxiv.org\/abs\/1503.02531"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467108"},{"key":"e_1_3_2_2_15_1","volume-title":"Categorical Reparameterization with Gumbel-Softmax. arXiv preprint arXiv:1611.01144","author":"Jang Eric","year":"2016","unstructured":"Eric Jang, Shixiang Gu, and Ben Poole. 2016. Categorical Reparameterization with Gumbel-Softmax. arXiv preprint arXiv:1611.01144 (2016)."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/2792838.2800172"},{"key":"e_1_3_2_2_17_1","volume-title":"Links, Text and Wikipedia","author":"Kaptein R","unstructured":"R Kaptein, M Koolen, and J Kamps. 2009. Result Diversity and Entity Ranking Experiments: Anchors, Links, Text and Wikipedia, University of Amsterdam. NIST Special Publication (2009), 500--278."},{"key":"e_1_3_2_2_18_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_19_1","volume-title":"Diversity in recommender systems--A survey. Knowledge-based systems 123","author":"Kunaver","year":"2017","unstructured":"Matev? Kunaver and Toma? Po?rl. 2017. Diversity in recommender systems--A survey. Knowledge-based systems 123 (2017), 154--162."},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539130"},{"key":"e_1_3_2_2_21_1","volume-title":"Optimization Techniques: Proceedings of the 8th IFIP Conference on Optimization Techniques W\u00fcrzburg, September 5--9","author":"Minoux Michel","year":"2005","unstructured":"Michel Minoux. 2005. Accelerated greedy algorithms for maximizing submodular set functions. In Optimization Techniques: Proceedings of the 8th IFIP Conference on Optimization Techniques W\u00fcrzburg, September 5--9, 1977. Springer, 234--243."},{"key":"e_1_3_2_2_22_1","volume-title":"Representation learning with contrastive predictive coding. arXiv preprint arXiv:1807.03748","author":"van den Oord Aaron","year":"2018","unstructured":"Aaron van den Oord, Yazhe Li, and Oriol Vinyals. 2018. Representation learning with contrastive predictive coding. arXiv preprint arXiv:1807.03748 (2018)."},{"key":"e_1_3_2_2_23_1","volume-title":"Neural nearest neighbors networks. Advances in Neural information processing systems 31","author":"Pl\u00f6tz Tobias","year":"2018","unstructured":"Tobias Pl\u00f6tz and Stefan Roth. 2018. Neural nearest neighbors networks. Advances in Neural information processing systems 31 (2018)."},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371783"},{"key":"e_1_3_2_2_25_1","first-page":"3868","article-title":"A framework for recommending relevant and diverse items","volume":"16","author":"Sha Chaofeng","year":"2016","unstructured":"Chaofeng Sha, XiaoweiWu, and Junyu Niu. 2016. A framework for recommending relevant and diverse items.. In IJCAI, Vol. 16. 3868--3874.","journal-title":"IJCAI"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00129"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.5555\/2627435.2670313"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3608767"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3511934"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599797"},{"key":"e_1_3_2_2_31_1","volume-title":"Optimization engineering techniques for the exact solution of NP-hard combinatorial optimization problems. European journal of operational research 125, 2","author":"Toth Paolo","year":"2000","unstructured":"Paolo Toth. 2000. Optimization engineering techniques for the exact solution of NP-hard combinatorial optimization problems. European journal of operational research 125, 2 (2000), 222--238."},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2014.2320500"},{"key":"e_1_3_2_2_33_1","volume-title":"Attention is all you need. Advances in neural information processing systems 30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, ?ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_2_34_1","volume-title":"Proceedings of the ADKDD'17","author":"Fu Bin","year":"2017","unstructured":"RuoxiWang, Bin Fu, Gang Fu, and MingliangWang. 2017. Deep & cross network for ad click predictions. In Proceedings of the ADKDD'17. 1--7."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467249"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3272018"},{"key":"e_1_3_2_2_37_1","volume-title":"Recent advances in diversified recommendation. arXiv preprint arXiv:1905.06589","author":"Liu Yong","year":"2019","unstructured":"QiongWu, Yong Liu, Chunyan Miao, Yin Zhao, Lu Guan, and Haihong Tang. 2019. Recent advances in diversified recommendation. arXiv preprint arXiv:1905.06589 (2019)."},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313727"},{"key":"e_1_3_2_2_39_1","volume-title":"Make Your Home Safe: Time-aware Unsupervised User Behavior Anomaly Detection in Smart Homes via Loss-guided Mask. arXiv preprint arXiv:2406.10928","author":"Xiao Jingyu","year":"2024","unstructured":"Jingyu Xiao, Zhiyao Xu, Qingsong Zou, Qing Li, Dan Zhao, Dong Fang, Ruoyu Li, Wenxin Tang, Kang Li, Xudong Zuo, Penghui Hu, Yong Jiang, Zixuan Weng, and Michael Lyv.R. 2024. Make Your Home Safe: Time-aware Unsupervised User Behavior Anomaly Detection in Smart Homes via Loss-guided Mask. arXiv preprint arXiv:2406.10928 (2024). https:\/\/arxiv.org\/abs\/2406.10928"},{"key":"e_1_3_2_2_40_1","volume-title":"Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems (AAMAS). 1634--1642","author":"Xiao Jingyu","year":"2023","unstructured":"Jingyu Xiao, Qingsong Zou, Qing Li, Dan Zhao, Kang Li, Wenxin Tang, Runjie Zhou, and Yong Jiang. 2023. User Device Interaction Prediction via Relational Gated Graph Attention Network and Intent-aware Encoder. In Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems (AAMAS). 1634--1642."},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3610906","article-title":"I Know Your Intent: Graph-enhanced Intent-aware User Device Interaction Prediction via Contrastive Learning","volume":"7","author":"Xiao Jingyu","year":"2023","unstructured":"Jingyu Xiao, Qingsong Zou, Qing Li, Dan Zhao, Kang Li, ZixuanWeng, Ruoyu Li, and Yong Jiang. 2023. I Know Your Intent: Graph-enhanced Intent-aware User Device Interaction Prediction via Contrastive Learning. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMUWT\/UbiComp) 7, 3 (2023), 1--28.","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMUWT\/UbiComp)"},{"key":"e_1_3_2_2_42_1","volume-title":"Reparameterizable subset sampling via continuous relaxations. arXiv preprint arXiv:1901.10517","author":"Xie Sang Michael","year":"2019","unstructured":"Sang Michael Xie and Stefano Ermon. 2019. Reparameterizable subset sampling via continuous relaxations. arXiv preprint arXiv:1901.10517 (2019)."},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1039\/C5TA02730F"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"crossref","unstructured":"Yue Xu Hao Chen Zefan Wang Jianwen Yin Qijie Shen Dimin Wang Feiran Huang Lixiang Lai Tao Zhuang Junfeng Ge et al. 2023. Multi-factor Sequential Re-ranking with Perception-Aware Diversification. arXiv preprint arXiv:2305.12420 (2023).","DOI":"10.1145\/3580305.3599869"},{"key":"e_1_3_2_2_45_1","volume-title":"A survey on causal inference. ACM Transactions on Knowledge Discovery from Data (TKDD) 15, 5","author":"Yao Liuyi","year":"2021","unstructured":"Liuyi Yao, Zhixuan Chu, Sheng Li, Yaliang Li, Jing Gao, and Aidong Zhang. 2021. A survey on causal inference. ACM Transactions on Knowledge Discovery from Data (TKDD) 15, 5 (2021), 1--46."},{"key":"e_1_3_2_2_46_1","unstructured":"Feng Yu. 2020. TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation. In International ACM SIGIR Conference on Research and Development in Information Retrieval. Xi'an China. https:\/\/ar5iv.org\/abs\/2005.02844"},{"key":"e_1_3_2_2_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539597.3570389"},{"key":"e_1_3_2_2_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3450086"},{"key":"e_1_3_2_2_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3511953"},{"key":"e_1_3_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449835"}],"event":{"name":"KDD '24: The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Barcelona Spain","acronym":"KDD '24","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671514","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3637528.3671514","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:04:18Z","timestamp":1750291458000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671514"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,24]]},"references-count":50,"alternative-id":["10.1145\/3637528.3671514","10.1145\/3637528"],"URL":"https:\/\/doi.org\/10.1145\/3637528.3671514","relation":{},"subject":[],"published":{"date-parts":[[2024,8,24]]},"assertion":[{"value":"2024-08-24","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}