{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T03:55:42Z","timestamp":1783137342950,"version":"3.54.6"},"publisher-location":"New York, NY, USA","reference-count":50,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,7,25]],"date-time":"2020-07-25T00:00:00Z","timestamp":1595635200000},"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":[[2020,7,25]]},"DOI":"10.1145\/3397271.3401181","type":"proceedings-article","created":{"date-parts":[[2020,7,25]],"date-time":"2020-07-25T07:50:08Z","timestamp":1595663408000},"page":"749-758","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":96,"title":["Neural Interactive Collaborative Filtering"],"prefix":"10.1145","author":[{"given":"Lixin","family":"Zou","sequence":"first","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Long","family":"Xia","sequence":"additional","affiliation":[{"name":"York University, Toronto, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yulong","family":"Gu","sequence":"additional","affiliation":[{"name":"JD.com, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangyu","family":"Zhao","sequence":"additional","affiliation":[{"name":"Michigan State University, East Lansing, MI, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weidong","family":"Liu","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jimmy Xiangji","family":"Huang","sequence":"additional","affiliation":[{"name":"York University, Toronto, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dawei","family":"Yin","sequence":"additional","affiliation":[{"name":"Baidu Inc., Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2020,7,25]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331199"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553380"},{"key":"e_1_3_2_1_3_1","volume-title":"NIPS'11","author":"Chapelle Olivier","year":"2011","unstructured":"Olivier Chapelle and Lihong Li . 2011 . An empirical evaluation of thompson sampling . In NIPS'11 . 2249--2257. Olivier Chapelle and Lihong Li. 2011. An empirical evaluation of thompson sampling. In NIPS'11. 2249--2257."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3290999"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/293"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159668"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2988450.2988454"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052585"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/1390334.1390446"},{"key":"e_1_3_2_1_10_1","volume-title":"RL2: Fast reinforcement learning via slow reinforcement learning. arXiv preprint arXiv:1611.02779","author":"Duan Yan","year":"2016","unstructured":"Yan Duan , John Schulman , Xi Chen , Peter L Bartlett , Ilya Sutskever , and Pieter Abbeel . 2016. RL2: Fast reinforcement learning via slow reinforcement learning. arXiv preprint arXiv:1611.02779 ( 2016 ). Yan Duan, John Schulman, Xi Chen, Peter L Bartlett, Ilya Sutskever, and Pieter Abbeel. 2016. RL2: Fast reinforcement learning via slow reinforcement learning. arXiv preprint arXiv:1611.02779 (2016)."},{"key":"e_1_3_2_1_11_1","volume-title":"Deep reinforcement learning in large discrete action spaces. arXiv preprint arXiv:1512.07679","author":"Dulac-Arnold Gabriel","year":"2015","unstructured":"Gabriel Dulac-Arnold , Richard Evans , Hado van Hasselt , Peter Sunehag , Timothy Lillicrap , Jonathan Hunt , Timothy Mann , TheophaneWeber, Thomas Degris , and Ben Coppin . 2015. Deep reinforcement learning in large discrete action spaces. arXiv preprint arXiv:1512.07679 ( 2015 ). Gabriel Dulac-Arnold, Richard Evans, Hado van Hasselt, Peter Sunehag, Timothy Lillicrap, Jonathan Hunt, Timothy Mann, TheophaneWeber, Thomas Degris, and Ben Coppin. 2015. Deep reinforcement learning in large discrete action spaces. arXiv preprint arXiv:1512.07679 (2015)."},{"key":"e_1_3_2_1_12_1","volume-title":"ICML'17","author":"Finn Chelsea","year":"2017","unstructured":"Chelsea Finn , Pieter Abbeel , and Sergey Levine . 2017 . Model-agnostic metalearning for fast adaptation of deep networks . In ICML'17 . JMLR, 1126--1135. Chelsea Finn, Pieter Abbeel, and Sergey Levine. 2017. Model-agnostic metalearning for fast adaptation of deep networks. In ICML'17. JMLR, 1126--1135."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159687"},{"key":"e_1_3_2_1_14_1","volume-title":"Hierarchical User Profiling for E-commerce Recommender Systems. In WSDM'20","author":"Gu Yulong","year":"2020","unstructured":"Yulong Gu , Zhuoye Ding , Shuaiqiang Wang , and Dawei Yin . 2020 . Hierarchical User Profiling for E-commerce Recommender Systems. In WSDM'20 . 223--231. Yulong Gu, Zhuoye Ding, Shuaiqiang Wang, and Dawei Yin. 2020. Hierarchical User Profiling for E-commerce Recommender Systems. In WSDM'20. 223--231."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2016.0110"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052569"},{"key":"e_1_3_2_1_17_1","first-page":"1457","article-title":"Non-negative matrix factorization with sparseness constraints","author":"Hoyer Patrik O","year":"2004","unstructured":"Patrik O Hoyer . 2004 . Non-negative matrix factorization with sparseness constraints . Journal of machine learning research 5 , Nov (2004), 1457 -- 1469 . Patrik O Hoyer. 2004. Non-negative matrix factorization with sparseness constraints. Journal of machine learning research 5, Nov (2004), 1457--1469.","journal-title":"Journal of machine learning research 5"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2018.00035"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-34106-9_18"},{"key":"e_1_3_2_1_20_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). Diederik P Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)."},{"key":"e_1_3_2_1_21_1","volume-title":"ICML'15 deep learning workshop","volume":"2","author":"Koch Gregory","year":"2015","unstructured":"Gregory Koch , Richard Zemel , and Ruslan Salakhutdinov . 2015 . Siamese neural networks for one-shot image recognition . In ICML'15 deep learning workshop , Vol. 2 . Gregory Koch, Richard Zemel, and Ruslan Salakhutdinov. 2015. Siamese neural networks for one-shot image recognition. In ICML'15 deep learning workshop, Vol. 2."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330859"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132926"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772758"},{"key":"e_1_3_2_1_26_1","volume-title":"NIPS'08","author":"Mnih Andriy","year":"2008","unstructured":"Andriy Mnih and Ruslan R Salakhutdinov . 2008 . Probabilistic matrix factorization . In NIPS'08 . 1257--1264. Andriy Mnih and Ruslan R Salakhutdinov. 2008. Probabilistic matrix factorization. In NIPS'08. 1257--1264."},{"key":"e_1_3_2_1_27_1","volume-title":"Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602","author":"Mnih Volodymyr","year":"2013","unstructured":"Volodymyr Mnih , Koray Kavukcuoglu , David Silver , Alex Graves , Ioannis Antonoglou , Daan Wierstra , and Martin Riedmiller . 2013. Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602 ( 2013 ). Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin Riedmiller. 2013. Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602 (2013)."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331268"},{"key":"e_1_3_2_1_29_1","volume-title":"SDM'14","author":"Qin Lijing","unstructured":"Lijing Qin , Shouyuan Chen , and Xiaoyan Zhu . 2014. Contextual combinatorial bandit and its application on diversified online recommendation . In SDM'14 . SIAM , 461--469. Lijing Qin, Shouyuan Chen, and Xiaoyan Zhu. 2014. Contextual combinatorial bandit and its application on diversified online recommendation. In SDM'14. SIAM, 461--469."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2010.127"},{"key":"e_1_3_2_1_31_1","volume-title":"BPR: Bayesian personalized ranking from implicit feedback. In UAI'09","author":"Rendle Steffen","year":"2009","unstructured":"Steffen Rendle , Christoph Freudenthaler , Zeno Gantner , and Lars Schmidt-Thieme . 2009 . BPR: Bayesian personalized ranking from implicit feedback. In UAI'09 . AUAI Press , 452--461. Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2009. BPR: Bayesian personalized ranking from implicit feedback. In UAI'09. AUAI Press, 452--461."},{"key":"e_1_3_2_1_32_1","volume-title":"ICML'16","author":"Santoro Adam","year":"2016","unstructured":"Adam Santoro , Sergey Bartunov , MatthewBotvinick, Daan Wierstra , and Timothy Lillicrap . 2016 . Meta-learning with memory-augmented neural networks . In ICML'16 . JMLR, 1842--1850. Adam Santoro, Sergey Bartunov, MatthewBotvinick, Daan Wierstra, and Timothy Lillicrap. 2016. Meta-learning with memory-augmented neural networks. In ICML'16. JMLR, 1842--1850."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"crossref","unstructured":"Harald Steck Roelof van Zwol and Chris Johnson. 2015. Interactive recommender systems: Tutorial. In RecSys'15. ACM 359--360.  Harald Steck Roelof van Zwol and Chris Johnson. 2015. Interactive recommender systems: Tutorial. In RecSys'15. ACM 359--360.","DOI":"10.1145\/2792838.2792840"},{"key":"e_1_3_2_1_34_1","volume-title":"Reinforcement learning: An introduction","author":"Sutton Richard S","unstructured":"Richard S Sutton and Andrew G Barto . 2018. Reinforcement learning: An introduction . MIT press . Richard S Sutton and Andrew G Barto. 2018. Reinforcement learning: An introduction. MIT press."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159656"},{"key":"e_1_3_2_1_36_1","volume-title":"NIPS'17","author":"Vartak Manasi","year":"2017","unstructured":"Manasi Vartak , Arvind Thiagarajan , Conrado Miranda , Jeshua Bratman , and Hugo Larochelle . 2017 . A meta-learning perspective on cold-start recommendations for items . In NIPS'17 . 6904--6914. Manasi Vartak, Arvind Thiagarajan, Conrado Miranda, Jeshua Bratman, and Hugo Larochelle. 2017. A meta-learning perspective on cold-start recommendations for items. In NIPS'17. 6904--6914."},{"key":"e_1_3_2_1_37_1","volume-title":"NIPS'17","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 . In NIPS'17 . 5998--6008. Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. In NIPS'17. 5998--6008."},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783273"},{"key":"e_1_3_2_1_39_1","volume-title":"AAAI'17","year":"2017","unstructured":"HuazhengWang, QingyunWu, and HongningWang. 2017 . Factorization Bandits for Interactive Recommendation .. In AAAI'17 . 2695--2702. HuazhengWang, QingyunWu, and HongningWang. 2017. Factorization Bandits for Interactive Recommendation.. In AAAI'17. 2695--2702."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3133025"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/2835776.2835837"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/447"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939878"},{"key":"e_1_3_2_1_44_1","unstructured":"Xiangyu Zhao Long Xia Liang Zhang Zhuoye Ding Dawei Yin and Jiliang Tang. 2018. Deep reinforcement learning for page-wise recommendations. In RecSys'18. ACM 95--103.  Xiangyu Zhao Long Xia Liang Zhang Zhuoye Ding Dawei Yin and Jiliang Tang. 2018. Deep reinforcement learning for page-wise recommendations. In RecSys'18. ACM 95--103."},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219886"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/2505515.2505690"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219823"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330668"},{"key":"e_1_3_2_1_49_1","volume-title":"DASFAA' 19","author":"Zou Lixin","unstructured":"Lixin Zou , Long Xia , Zhuoye Ding , Dawei Yin , Jiaxing Song , and Weidong Liu . 2019. Reinforcement Learning to Diversify Top-N Recommendation . In DASFAA' 19 . Springer , 104--120. Lixin Zou, Long Xia, Zhuoye Ding, Dawei Yin, Jiaxing Song, and Weidong Liu. 2019. Reinforcement Learning to Diversify Top-N Recommendation. In DASFAA' 19. Springer, 104--120."},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371801"}],"event":{"name":"SIGIR '20: The 43rd International ACM SIGIR conference on research and development in Information Retrieval","location":"Virtual Event China","acronym":"SIGIR '20","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3397271.3401181","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3397271.3401181","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:41:43Z","timestamp":1750200103000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3397271.3401181"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,25]]},"references-count":50,"alternative-id":["10.1145\/3397271.3401181","10.1145\/3397271"],"URL":"https:\/\/doi.org\/10.1145\/3397271.3401181","relation":{},"subject":[],"published":{"date-parts":[[2020,7,25]]},"assertion":[{"value":"2020-07-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}