{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T15:18:45Z","timestamp":1777735125802,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":54,"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"}],"funder":[{"name":"National Nature Science Foundation of China","award":["61672241, U1611461"],"award-info":[{"award-number":["61672241, U1611461"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["x2js-D2192830"],"award-info":[{"award-number":["x2js-D2192830"]}]},{"name":"Natural Science Foundation of Guangdong Province","award":["2016A030308013"],"award-info":[{"award-number":["2016A030308013"]}]},{"name":"Major Project of National Social Science Foundation of China","award":["18ZDA062"],"award-info":[{"award-number":["18ZDA062"]}]},{"name":"Science and Technology Program of Guangdong Province","award":["2019A050510010"],"award-info":[{"award-number":["2019A050510010"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,7,25]]},"DOI":"10.1145\/3397271.3401445","type":"proceedings-article","created":{"date-parts":[[2020,7,25]],"date-time":"2020-07-25T07:50:08Z","timestamp":1595663408000},"page":"2397-2406","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":142,"title":["Multiplex Behavioral Relation Learning for Recommendation via Memory Augmented Transformer Network"],"prefix":"10.1145","author":[{"given":"Lianghao","family":"Xia","sequence":"first","affiliation":[{"name":"South China University of Technology, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chao","family":"Huang","sequence":"additional","affiliation":[{"name":"JD Finance America Corporation, Mountain View, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Xu","sequence":"additional","affiliation":[{"name":"South China University of Technology &amp; Peng Cheng Laboratory, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Dai","sequence":"additional","affiliation":[{"name":"JD Finance America Corporation, Mountain View, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Zhang","sequence":"additional","affiliation":[{"name":"Boshi Qiangzhi Science and Technology Co., Ltd, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liefeng","family":"Bo","sequence":"additional","affiliation":[{"name":"JD Finance America Corporation, Mountain View, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,7,25]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"crossref","unstructured":"Kristen M Altenburger and Daniel E Ho. 2019. Is Yelp Actually Cleaning Up the Restaurant Industry? A Re-Analysis on the Relative Usefulness of Consumer Reviews. In WWW. 2543--2550. Kristen M Altenburger and Daniel E Ho. 2019. Is Yelp Actually Cleaning Up the Restaurant Industry? A Re-Analysis on the Relative Usefulness of Consumer Reviews. In WWW. 2543--2550.","DOI":"10.1145\/3308558.3313683"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"crossref","unstructured":"Yukuo Cen Xu Zou Jianwei Zhang Hongxia Yang Jingren Zhou and Jie Tang. 2019. Representation learning for attributed multiplex heterogeneous network. In KDD. 1358--1368. Yukuo Cen Xu Zou Jianwei Zhang Hongxia Yang Jingren Zhou and Jie Tang. 2019. Representation learning for attributed multiplex heterogeneous network. In KDD. 1358--1368.","DOI":"10.1145\/3292500.3330964"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"crossref","unstructured":"Chong Chen Min Zhang Yiqun Liu and Shaoping Ma. 2019. Social attentional memory network: Modeling aspect-and friend-level differences in recommendation. In WSDM. 177--185. Chong Chen Min Zhang Yiqun Liu and Shaoping Ma. 2019. Social attentional memory network: Modeling aspect-and friend-level differences in recommendation. In WSDM. 177--185.","DOI":"10.1145\/3289600.3290982"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"crossref","unstructured":"Xu Chen Hongteng Xu Yongfeng Zhang Jiaxi Tang Yixin Cao Zheng Qin and Hongyuan Zha. 2018. Sequential recommendation with user memory networks. In WSDM. ACM 108--116. Xu Chen Hongteng Xu Yongfeng Zhang Jiaxi Tang Yixin Cao Zheng Qin and Hongyuan Zha. 2018. Sequential recommendation with user memory networks. In WSDM. ACM 108--116.","DOI":"10.1145\/3159652.3159668"},{"key":"e_1_3_2_2_5_1","unstructured":"Chao Du Chongxuan Li Yin Zheng Jun Zhu and Bo Zhang. 2018. Collaborative filtering with user-item co-autoregressive models. In AAAI. Chao Du Chongxuan Li Yin Zheng Jun Zhu and Bo Zhang. 2018. Collaborative filtering with user-item co-autoregressive models. In AAAI."},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"crossref","unstructured":"Wenqi Fan Yao Ma Qing Li Yuan He Eric Zhao Jiliang Tang and Dawei Yin. 2019. Graph Neural Networks for Social Recommendation. In WWW. ACM 417--426. Wenqi Fan Yao Ma Qing Li Yuan He Eric Zhao Jiliang Tang and Dawei Yin. 2019. Graph Neural Networks for Social Recommendation. In WWW. ACM 417--426.","DOI":"10.1145\/3308558.3313488"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2019.00140"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"crossref","unstructured":"Long Guo Lifeng Hua Rongfei Jia Binqiang Zhao Xiaobo Wang and Bin Cui. 2019. Buying or Browsing?: Predicting Real-time Purchasing Intent using Attention-based Deep Network with Multiple Behavior. In KDD. 1984--1992. Long Guo Lifeng Hua Rongfei Jia Binqiang Zhao Xiaobo Wang and Bin Cui. 2019. Buying or Browsing?: Predicting Real-time Purchasing Intent using Attention-based Deep Network with Multiple Behavior. In KDD. 1984--1992.","DOI":"10.1145\/3292500.3330670"},{"key":"e_1_3_2_2_9_1","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016b. Deep residual learning for image recognition. In CVPR. 770--778. Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016b. Deep residual learning for image recognition. In CVPR. 770--778."},{"key":"e_1_3_2_2_10_1","unstructured":"Xiangnan He and Tat-Seng Chua. 2017. Neural factorization machines for sparse predictive analytics. In SIGIR. ACM 355--364. Xiangnan He and Tat-Seng Chua. 2017. Neural factorization machines for sparse predictive analytics. In SIGIR. ACM 355--364."},{"key":"e_1_3_2_2_11_1","unstructured":"Xiangnan He Lizi Liao Hanwang Zhang Liqiang Nie Xia Hu and Tat-Seng Chua. 2017. Neural collaborative filtering. In WWW. 173--182. Xiangnan He Lizi Liao Hanwang Zhang Liqiang Nie Xia Hu and Tat-Seng Chua. 2017. Neural collaborative filtering. In WWW. 173--182."},{"key":"e_1_3_2_2_12_1","unstructured":"Xiangnan He Hanwang Zhang Min-Yen Kan and Tat-Seng Chua. 2016a. Fast matrix factorization for online recommendation with implicit feedback. In SIGIR. 549--558. Xiangnan He Hanwang Zhang Min-Yen Kan and Tat-Seng Chua. 2016a. Fast matrix factorization for online recommendation with implicit feedback. In SIGIR. 549--558."},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"crossref","unstructured":"Chao Huang Xian Wu Xuchao Zhang Chuxu Zhang Jiashu Zhao Dawei Yin and Nitesh V Chawla. 2019. Online Purchase Prediction via Multi-Scale Modeling of Behavior Dynamics. In KDD. 2613--2622. Chao Huang Xian Wu Xuchao Zhang Chuxu Zhang Jiashu Zhao Dawei Yin and Nitesh V Chawla. 2019. Online Purchase Prediction via Multi-Scale Modeling of Behavior Dynamics. In KDD. 2613--2622.","DOI":"10.1145\/3292500.3330790"},{"key":"e_1_3_2_2_14_1","volume-title":"Self-attentive sequential recommendation","author":"Kang Wang-Cheng","unstructured":"Wang-Cheng Kang and Julian McAuley . 2018. Self-attentive sequential recommendation . In ICDM. IEEE , 197--206. Wang-Cheng Kang and Julian McAuley. 2018. Self-attentive sequential recommendation. In ICDM. IEEE, 197--206."},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_2_16_1","unstructured":"Chao Li Zhiyuan Liu Mengmeng Wu Yuchi Xu Huan Zhao Pipei Huang Guoliang Kang Qiwei Chen Wei Li and Dik Lun Lee. 2019. Multi-interest network with dynamic routing for recommendation at Tmall. In CIKM. 2615--2623. Chao Li Zhiyuan Liu Mengmeng Wu Yuchi Xu Huan Zhao Pipei Huang Guoliang Kang Qiwei Chen Wei Li and Dik Lun Lee. 2019. Multi-interest network with dynamic routing for recommendation at Tmall. In CIKM. 2615--2623."},{"key":"e_1_3_2_2_17_1","unstructured":"Jing Li Pengjie Ren Zhumin Chen Zhaochun Ren Tao Lian and Jun Ma. 2017. Neural attentive session-based recommendation. In CIKM. 1419--1428. Jing Li Pengjie Ren Zhumin Chen Zhaochun Ren Tao Lian and Jun Ma. 2017. Neural attentive session-based recommendation. In CIKM. 1419--1428."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"crossref","unstructured":"Daryl Lim Julian McAuley and Gert Lanckriet. 2015. Top-n recommendation with missing implicit feedback. In Recsys. 309--312. Daryl Lim Julian McAuley and Gert Lanckriet. 2015. Top-n recommendation with missing implicit feedback. In Recsys. 309--312.","DOI":"10.1145\/2792838.2799671"},{"key":"e_1_3_2_2_19_1","unstructured":"Chenghao Liu Tao Lu Xin Wang Zhiyong Cheng Jianling Sun and Steven CH Hoi. 2019. Compositional Coding for Collaborative Filtering. In SIGIR. 145--154. Chenghao Liu Tao Lu Xin Wang Zhiyong Cheng Jianling Sun and Steven CH Hoi. 2019. Compositional Coding for Collaborative Filtering. In SIGIR. 145--154."},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3291756"},{"key":"e_1_3_2_2_21_1","unstructured":"Chen Ma Liheng Ma Yingxue Zhang Jianing Sun Xue Liu and Mark Coates. 2020. Memory Augmented Graph Neural Networks for Sequential Recommendation. In AAAI. Chen Ma Liheng Ma Yingxue Zhang Jianing Sun Xue Liu and Mark Coates. 2020. Memory Augmented Graph Neural Networks for Sequential Recommendation. In AAAI."},{"key":"e_1_3_2_2_22_1","unstructured":"Andriy Mnih and etal 2008. Probabilistic matrix factorization. In NIPS. 1257--1264. Andriy Mnih and et al. 2008. Probabilistic matrix factorization. In NIPS. 1257--1264."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3291016"},{"key":"e_1_3_2_2_24_1","volume-title":"Eugenio Di Sciascio, and Roberto Mirizzi.","author":"Ostuni Vito Claudio","year":"2013","unstructured":"Vito Claudio Ostuni , Tommaso Di Noia , Eugenio Di Sciascio, and Roberto Mirizzi. 2013 . Top-n recommendations from implicit feedback leveraging linked open data. In Recsys . 85--92. Vito Claudio Ostuni, Tommaso Di Noia, Eugenio Di Sciascio, and Roberto Mirizzi. 2013. Top-n recommendations from implicit feedback leveraging linked open data. In Recsys. 85--92."},{"key":"e_1_3_2_2_25_1","unstructured":"Jiarui Qin Kan Ren Yuchen Fang Weinan Zhang and Yong Yu. 2020. Sequential Recommendation with Dual Side Neighbor-based Collaborative Relation Modeling. In WSDM. 465--473. Jiarui Qin Kan Ren Yuchen Fang Weinan Zhang and Yong Yu. 2020. Sequential Recommendation with Dual Side Neighbor-based Collaborative Relation Modeling. In WSDM. 465--473."},{"key":"e_1_3_2_2_26_1","volume-title":"BPR: Bayesian personalized ranking from implicit feedback. In UAI.","author":"Rendle Steffen","year":"2012","unstructured":"Steffen Rendle , Christoph Freudenthaler , Zeno Gantner , and Lars Schmidt-Thieme . 2012 . BPR: Bayesian personalized ranking from implicit feedback. In UAI. Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2012. BPR: Bayesian personalized ranking from implicit feedback. In UAI."},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/2740908.2742726"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"crossref","unstructured":"Weiping Song Zhiping Xiao Yifan Wang Laurent Charlin Ming Zhang and Jian Tang. 2019. Session-based social recommendation via dynamic graph attention networks. In WSDM. 555--563. Weiping Song Zhiping Xiao Yifan Wang Laurent Charlin Ming Zhang and Jian Tang. 2019. Session-based social recommendation via dynamic graph attention networks. In WSDM. 555--563.","DOI":"10.1145\/3289600.3290989"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"crossref","unstructured":"Florian Strub Romaric Gaudel and J\u00e9r\u00e9mie Mary. 2016. Hybrid recommender system based on autoencoders. In DLRS. 11--16. Florian Strub Romaric Gaudel and J\u00e9r\u00e9mie Mary. 2016. Hybrid recommender system based on autoencoders. In DLRS. 11--16.","DOI":"10.1145\/2988450.2988456"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"crossref","unstructured":"Fei Sun Jun Liu Jian Wu Changhua Pei Xiao Lin Wenwu Ou and Peng Jiang. 2019 a. BERT4Rec: Sequential recommendation with bidirectional encoder representations from transformer. In CIKM. 1441--1450. Fei Sun Jun Liu Jian Wu Changhua Pei Xiao Lin Wenwu Ou and Peng Jiang. 2019 a. BERT4Rec: Sequential recommendation with bidirectional encoder representations from transformer. In CIKM. 1441--1450.","DOI":"10.1145\/3357384.3357895"},{"key":"e_1_3_2_2_31_1","volume-title":"2019 b. Multi-Graph Convolution Collaborative Filtering","author":"Sun Jianing","unstructured":"Jianing Sun , Yingxue Zhang , Chen Ma , Mark Coates , Huifeng Guo , Ruiming Tang , and Xiuqiang He . 2019 b. Multi-Graph Convolution Collaborative Filtering . In ICDM. IEEE , 1306--1311. Jianing Sun, Yingxue Zhang, Chen Ma, Mark Coates, Huifeng Guo, Ruiming Tang, and Xiuqiang He. 2019 b. Multi-Graph Convolution Collaborative Filtering. In ICDM. IEEE, 1306--1311."},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"crossref","unstructured":"Jiaxi Tang and Ke Wang. 2018. Personalized top-n sequential recommendation via convolutional sequence embedding. In WSDM. 565--573. Jiaxi Tang and Ke Wang. 2018. Personalized top-n sequential recommendation via convolutional sequence embedding. In WSDM. 565--573.","DOI":"10.1145\/3159652.3159656"},{"key":"e_1_3_2_2_33_1","volume-title":"Luu Anh Tuan, and Siu Cheung Hui","author":"Tay Yi","year":"2018","unstructured":"Yi Tay , Luu Anh Tuan, and Siu Cheung Hui . 2018 a. Latent relational metric learning via memory-based attention for collaborative ranking. In WWW. 729--739. Yi Tay, Luu Anh Tuan, and Siu Cheung Hui. 2018a. Latent relational metric learning via memory-based attention for collaborative ranking. In WWW. 729--739."},{"key":"e_1_3_2_2_34_1","volume-title":"Anh Tuan Luu, and Siu Cheung Hui","author":"Tay Yi","year":"2018","unstructured":"Yi Tay , Anh Tuan Luu, and Siu Cheung Hui . 2018 b. Multi-pointer co-attention networks for recommendation. In KDD. 2309--2318. Yi Tay, Anh Tuan Luu, and Siu Cheung Hui. 2018b. Multi-pointer co-attention networks for recommendation. In KDD. 2309--2318."},{"key":"e_1_3_2_2_35_1","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. 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. 5998--6008."},{"key":"e_1_3_2_2_36_1","volume-title":"Yi Tay, Yiding Liu, Gao Cong, and Xiaoli Li.","author":"Tran Lucas Vinh","year":"2019","unstructured":"Lucas Vinh Tran , Tuan-Anh Nguyen Pham , Yi Tay, Yiding Liu, Gao Cong, and Xiaoli Li. 2019 . Interact and decide: Medley of sub-attention networks for effective group recommendation. In SIGIR. 255--264. Lucas Vinh Tran, Tuan-Anh Nguyen Pham, Yi Tay, Yiding Liu, Gao Cong, and Xiaoli Li. 2019. Interact and decide: Medley of sub-attention networks for effective group recommendation. In SIGIR. 255--264."},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"crossref","unstructured":"Hongwei Wang Fuzheng Zhang Mengdi Zhang Jure Leskovec Miao Zhao Wenjie Li etal 2019 d. Knowledge-aware graph neural networks with label smoothness regularization for recommender systems. In KDD. 968--977. Hongwei Wang Fuzheng Zhang Mengdi Zhang Jure Leskovec Miao Zhao Wenjie Li et al. 2019 d. Knowledge-aware graph neural networks with label smoothness regularization for recommender systems. In KDD. 968--977.","DOI":"10.1145\/3292500.3330836"},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"crossref","unstructured":"Jianling Wang Raphael Louca Diane Hu Caitlin Cellier James Caverlee and Liangjie Hong. 2020. Time to Shop for Valentine's Day: Shopping Occasions and Sequential Recommendation in E-commerce. In WSDM. 645--653. Jianling Wang Raphael Louca Diane Hu Caitlin Cellier James Caverlee and Liangjie Hong. 2020. Time to Shop for Valentine's Day: Shopping Occasions and Sequential Recommendation in E-commerce. In WSDM. 645--653.","DOI":"10.1145\/3336191.3371836"},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"crossref","unstructured":"Weixun Wang Junqi Jin Jianye Hao Chunjie Chen Chuan Yu Weinan Zhang Jun Wang Xiaotian Hao Yixi Wang Han Li etal 2019 c. Learning Adaptive Display Exposure for Real-Time Advertising. In CIKM. 2595--2603. Weixun Wang Junqi Jin Jianye Hao Chunjie Chen Chuan Yu Weinan Zhang Jun Wang Xiaotian Hao Yixi Wang Han Li et al. 2019 c. Learning Adaptive Display Exposure for Real-Time Advertising. In CIKM. 2595--2603.","DOI":"10.1145\/3357384.3357806"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"crossref","unstructured":"Xiang Wang Xiangnan He Yixin Cao Meng Liu and Tat-Seng Chua. 2019 a. Kgat: Knowledge graph attention network for recommendation. In KDD. 950--958. Xiang Wang Xiangnan He Yixin Cao Meng Liu and Tat-Seng Chua. 2019 a. Kgat: Knowledge graph attention network for recommendation. In KDD. 950--958.","DOI":"10.1145\/3292500.3330989"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"crossref","unstructured":"Xiang Wang Xiangnan He Meng Wang Fuli Feng and Tat-Seng Chua. 2019 b. Neural Graph Collaborative Filtering. In SIGIR. Xiang Wang Xiangnan He Meng Wang Fuli Feng and Tat-Seng Chua. 2019 b. Neural Graph Collaborative Filtering. In SIGIR.","DOI":"10.1145\/3331184.3331267"},{"key":"e_1_3_2_2_42_1","unstructured":"Hongfa Wen Xin Liu Chenggang Yan Linhua Jiang Yaoqi Sun Jiyong Zhang and Haibing Yin. 2019. Leveraging Multiple Implicit Feedback for Personalized Recommendation with Neural Network. In AIAM. 1--6. Hongfa Wen Xin Liu Chenggang Yan Linhua Jiang Yaoqi Sun Jiyong Zhang and Haibing Yin. 2019. Leveraging Multiple Implicit Feedback for Personalized Recommendation with Neural Network. In AIAM. 1--6."},{"key":"e_1_3_2_2_43_1","unstructured":"Chuhan Wu Fangzhao Wu Suyu Ge Tao Qi Yongfeng Huang and Xing Xie. 2019 b. Neural News Recommendation with Multi-Head Self-Attention. In EMNLP. 6390--6395. Chuhan Wu Fangzhao Wu Suyu Ge Tao Qi Yongfeng Huang and Xing Xie. 2019 b. Neural News Recommendation with Multi-Head Self-Attention. In EMNLP. 6390--6395."},{"key":"e_1_3_2_2_44_1","unstructured":"Xian Wu Baoxu Shi Yuxiao Dong Chao Huang and Nitesh V Chawla. 2019 a. Neural tensor factorization for temporal interaction learning. In WSDM. 537--545. Xian Wu Baoxu Shi Yuxiao Dong Chao Huang and Nitesh V Chawla. 2019 a. Neural tensor factorization for temporal interaction learning. In WSDM. 537--545."},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"crossref","unstructured":"Yao Wu Christopher DuBois Alice X Zheng etal 2016. Collaborative denoising auto-encoders for top-n recommender systems. In WSDM. ACM 153--162. Yao Wu Christopher DuBois Alice X Zheng et al. 2016. Collaborative denoising auto-encoders for top-n recommender systems. In WSDM. ACM 153--162.","DOI":"10.1145\/2835776.2835837"},{"key":"e_1_3_2_2_46_1","doi-asserted-by":"crossref","unstructured":"Xin Xin Xiangnan He Yongfeng Zhang Yongdong Zhang and Joemon Jose. 2019. Relational Collaborative Filtering: Modeling Multiple Item Relations for Recommendation. In SIGIR. Xin Xin Xiangnan He Yongfeng Zhang Yongdong Zhang and Joemon Jose. 2019. Relational Collaborative Filtering: Modeling Multiple Item Relations for Recommendation. In SIGIR.","DOI":"10.1145\/3331184.3331188"},{"key":"e_1_3_2_2_47_1","doi-asserted-by":"crossref","unstructured":"Hong-Jian Xue Xinyu Dai Jianbing Zhang Shujian Huang etal 2017. Deep Matrix Factorization Models for Recommender Systems.. In IJCAI. 3203--3209. Hong-Jian Xue Xinyu Dai Jianbing Zhang Shujian Huang et al. 2017. Deep Matrix Factorization Models for Recommender Systems.. In IJCAI. 3203--3209.","DOI":"10.24963\/ijcai.2017\/447"},{"key":"e_1_3_2_2_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331342"},{"key":"e_1_3_2_2_49_1","volume-title":"2019 a. STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems. IJCAI","author":"Zhang Jiani","year":"2019","unstructured":"Jiani Zhang , Xingjian Shi , Shenglin Zhao , and Irwin King . 2019 a. STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems. IJCAI ( 2019 ). Jiani Zhang, Xingjian Shi, Shenglin Zhao, and Irwin King. 2019 a. STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems. IJCAI (2019)."},{"key":"e_1_3_2_2_50_1","volume-title":"AAAI","volume":"9","author":"Zhang Shuai","year":"2019","unstructured":"Shuai Zhang , Yi Tay , Lina Yao , Aixin Sun , and Jake An . 2019 b. Next item recommendation with self-attentive metric learning . In AAAI , Vol. 9 . Shuai Zhang, Yi Tay, Lina Yao, Aixin Sun, and Jake An. 2019 b. Next item recommendation with self-attentive metric learning. In AAAI, Vol. 9."},{"key":"e_1_3_2_2_51_1","doi-asserted-by":"crossref","unstructured":"Lei Zheng Chaozhuo Li Chun-Ta Lu Jiawei Zhang and Philip S Yu. 2019. Deep Distribution Network: Addressing the Data Sparsity Issue for Top-N Recommendation. In SIGIR. 1081--1084. Lei Zheng Chaozhuo Li Chun-Ta Lu Jiawei Zhang and Philip S Yu. 2019. Deep Distribution Network: Addressing the Data Sparsity Issue for Top-N Recommendation. In SIGIR. 1081--1084.","DOI":"10.1145\/3331184.3331330"},{"key":"e_1_3_2_2_52_1","doi-asserted-by":"crossref","unstructured":"Lei Zheng Vahid Noroozi and Philip S Yu. 2017. Joint deep modeling of users and items using reviews for recommendation. In WSDM. 425--434. Lei Zheng Vahid Noroozi and Philip S Yu. 2017. Joint deep modeling of users and items using reviews for recommendation. In WSDM. 425--434.","DOI":"10.1145\/3018661.3018665"},{"key":"e_1_3_2_2_53_1","doi-asserted-by":"crossref","unstructured":"Yin Zheng Bangsheng Tang Wenkui Ding and Hanning Zhou. 2016. A neural autoregressive approach to collaborative filtering. In ICML. Yin Zheng Bangsheng Tang Wenkui Ding and Hanning Zhou. 2016. A neural autoregressive approach to collaborative filtering. In ICML.","DOI":"10.1145\/2988450.2988453"},{"key":"e_1_3_2_2_54_1","doi-asserted-by":"crossref","unstructured":"Guorui Zhou Xiaoqiang Zhu Chenru Song Ying Fan Han Zhu Xiao Ma Yanghui Yan Junqi Jin Han Li and Kun Gai. 2018. Deep interest network for click-through rate prediction. In KDD. 1059--1068. Guorui Zhou Xiaoqiang Zhu Chenru Song Ying Fan Han Zhu Xiao Ma Yanghui Yan Junqi Jin Han Li and Kun Gai. 2018. Deep interest network for click-through rate prediction. In KDD. 1059--1068.","DOI":"10.1145\/3219819.3219823"}],"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\/3397271.3401445","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3397271.3401445","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:41:48Z","timestamp":1750200108000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3397271.3401445"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,25]]},"references-count":54,"alternative-id":["10.1145\/3397271.3401445","10.1145\/3397271"],"URL":"https:\/\/doi.org\/10.1145\/3397271.3401445","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"}}]}}