{"id":113,"date":"2021-09-18T05:05:48","date_gmt":"2021-09-18T09:05:48","guid":{"rendered":"https:\/\/sites.nd.edu\/xiangliang-zhang\/?page_id=113"},"modified":"2026-01-29T20:48:07","modified_gmt":"2026-01-30T01:48:07","slug":"recommendation-systems","status":"publish","type":"page","link":"https:\/\/sites.nd.edu\/xiangliang-zhang\/recommendation-systems\/","title":{"rendered":"Recommendation Systems"},"content":{"rendered":"\n<p class=\"has-medium-font-size wp-block-paragraph\">We design machine learning based models for session-based recommendation, sequential recommendation, social recommendation, POI recommendation, safe recommendation, interpretable recommendation, and so on.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Manal A. Alshehri and Xiangliang Zhang. Unveiling the Dynamics of Multi-Dimensional Filter Bubbles in News Recommendation. Accepted as a short paper at <strong>IEEE BigData<\/strong> 2025.<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Manal Alshehri and Xiangliang Zhang. Forgetting User Preference in Recommendation Systems with Label-Flipping. Accepted for the 2023 IEEE<a href=\"https:\/\/bigdataieee.org\/BigData2023\/\" data-type=\"link\" data-id=\"https:\/\/bigdataieee.org\/BigData2023\/\"> <strong>International Conference on Big Data<\/strong><\/a>, Dec 15-18, 2023 @ Sorrento, Italy (Regular Paper, 92 out of 526 submissions = 17%)<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Ziyi Kou, Saurav Manchanda, Shih-Ting Lin, Min Xie, Haixun Wang and Xiangliang Zhang. Modeling Sequential Collaborative User Behaviors for Seller-aware Next Basket Recommendation. Accepted for publication in the <strong><a rel=\"noreferrer noopener\" href=\"https:\/\/uobevents.eventsair.com\/cikm2023\/\" data-type=\"URL\" data-id=\"https:\/\/uobevents.eventsair.com\/cikm2023\/\" target=\"_blank\">CIKM 2023<\/a><\/strong> proceeding. (Acceptance rate of 24%, 354 out of 1472 FULL paper submissions).<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Zhenwei Tang, Griffin Floto, Armin Toroghi, Shichao Pei, Xiangliang Zhang and Scott Sanner. LogicRec: Recommendation with Users&#8217; Logical Requirements. Accepted by <strong><a href=\"https:\/\/sigir.org\/sigir2023\/\" data-type=\"URL\" data-id=\"https:\/\/sigir.org\/sigir2023\/\">SIGIR 2023<\/a><\/strong> (Short paper, Acceptance rate = 154\/613 = 25.12%)<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Taicheng Guo, Lu Yu, Basem Shihada, Xiangliang Zhang. Few-shot News Recommendation via Cross-lingual Transfer. Accepted by <a href=\"https:\/\/www2023.thewebconf.org\/\" data-type=\"URL\" data-id=\"https:\/\/www2023.thewebconf.org\/\"><strong>The Web Conference 2023<\/strong><\/a>. Texas, USA on April 30 &#8211; May 4 2023. (Acceptance rate = 19.2%, 365 out of 1900 submissions)<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Manal Abdulaziz Alshehri, Xiangliang Zhang. Generative Adversarial Zero-Shot Learning for Cold-Start News Recommendation. Accepted as a full paper by <strong><a href=\"https:\/\/www.cikm2022.org\/\">CIKM 2022<\/a><\/strong>.<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Lu Yu, Shichao Pei, Feng Zhu, Longfei Li, Jun Zhou, Chuxu Zhang, Xiangliang Zhang. A Biased Sampling Method for Imbalanced Personalized Ranking. Accepted as a full paper by <strong><a href=\"https:\/\/www.cikm2022.org\/\">CIKM 2022<\/a><\/strong>.<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Junliang Yu, Hongzhi Yin, Min Gao, Xin Xia, Xiangliang Zhang, and Quoc Viet Hung Nguyen. Socially-Aware Self-Supervised Tri-Training for Recommendation. &nbsp;<a href=\"https:\/\/www.kdd.org\/kdd2021\/\">ACM SIGKDD Conference on Knowledge Discovery and Data Mining (<strong>KDD<\/strong> 2021)<\/a>\u200b. Virtual Conference, Aug 14-18, 2021. (Acceptance Rate = 238\/1541 = 15.4%)<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Xin Xia, Hongzhi Yin, Junliang Yu, Qinyong Wang, Lizhen Cui, and Xiangliang Zhang. Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation. In proceedings of&nbsp;<a href=\"https:\/\/aaai.org\/Conferences\/AAAI-21\/\">the Thirty-Fifth AAAI Conference on Artificial Intelligence (<strong>AAAI<\/strong> 2021)\u200b<\/a>&nbsp;\u200b (acceptance rate of 21%, 1692\/7911).<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Shijie Zhang, Hongzhi Yin, Tong Chen, Zi Huang, Lizhen Cui, and Xiangliang Zhang. Graph Embedding for Recommendation against Attribute Inference Attacks.&nbsp;<a href=\"https:\/\/www2021.thewebconf.org\/\">The Web Conference 2021 (<strong>WWW<\/strong>&#8217;21)<\/a>,\u200b April 2021. &nbsp;(acceptance rate of 20.6%, 357\/1736).<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Junliang Yu, Hongzhi Yin, Jundong Li, Qinyong Wang, Nguyen Quoc Viet Hung, and Xiangliang Zhang. Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation.&nbsp;<a href=\"https:\/\/www2021.thewebconf.org\/\">The Web Conference 2021 (<strong>WWW<\/strong>&#8217;21)<\/a>, April 2021. &nbsp;(acceptance rate of 20.6%, 357\/1736).<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Xuhui Ren, Hongzhi Yin, Tong Chen, Hao Wang, Nguyen Quoc Viet Hung, Zi Huang, Xiangliang Zhang.&nbsp;Crsal: Conversational recommender systems with adversarial learning.&nbsp;To appear in&nbsp;&nbsp;<a href=\"https:\/\/dl.acm.org\/journal\/tois\">ACM Transactions on Information Systems (<strong>TOIS<\/strong>)<\/a>, 2021.<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u200b\u200b\u200bBasmah Altaf, Uchenna Akujuobi, Lu Yu,&nbsp;Xiangliang Zhang. Dataset Recommendation via Variational Graph Autoencoder. The &nbsp;<a href=\"http:\/\/icdm2019.bigke.org\/\">19th IEEE International Conference on Data Mining&nbsp;(<strong>ICDM<\/strong> 2019)<\/a>,&nbsp;November 8-11, 2019,&nbsp;Beijing, China&nbsp;(Regular&nbsp;paper,&nbsp;Acceptance rate= 95\/1046&nbsp;9.08%).\u200b<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Yujun Chen, Yuanhong Wang, Yutao Zhang, Juhua Pu, &nbsp;Xiangliang Zhang. AMENDER: an Attentive and Aggregate Multi-layered Network for Dataset Recommendation. The&nbsp;<a href=\"http:\/\/icdm2019.bigke.org\/\">19th IEEE International Conference on Data Mining&nbsp;(<strong>ICDM<\/strong> 2019)<\/a>&nbsp;&nbsp;,&nbsp;November 8-11, 2019,&nbsp;Beijing, China (Short paper, Acceptance rate= 18.5%).\u200b<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Huafeng Liu, Liping Jing, Jingxuan Wen, Jian Yu,&nbsp;Xiangliang Zhang. In2Rec: In\ufb02uence-based Interpretable Recommendation. The 28th&nbsp;<a href=\"http:\/\/www.cikm2019.net\/\">ACM International Conference on Information and Knowledge Management (<strong>CIKM<\/strong> 2019)<\/a>,&nbsp;November 3rd-7th, 2019, Beijing, China&nbsp;(Acceptance rate=200\/1030=19.4%).<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Rui Yan, Ran Le, Yang Song, Tao Zhang,&nbsp;Xiangliang Zhang&nbsp;and Dongyan Zhao. Interview Choice Reveals Your Preference on the Market: To Improve Job-Resume Matching through Profiling Memories. In proceedings of&nbsp;<a href=\"https:\/\/www.kdd.org\/kdd2019\/\">the 25th SIGKDD Conference on Knowledge Discovery and Data Mining <strong>(KDD<\/strong> 2019)<\/a>&nbsp;,&nbsp; &nbsp;August 4 &#8211; 8, 2019 Anchorage, Alaska, USA&nbsp; (Acceptance rate ~170\/1200=14.2%).<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>&nbsp;Lu Yu,&nbsp;Chuxu Zhang,&nbsp;&nbsp;Shangsong Liang,&nbsp;and&nbsp;Xiangliang Zhang.&nbsp;Multi-order Attentive Ranking Model for Sequential Recommendation.&nbsp;&nbsp;In proceedings of&nbsp;<a href=\"https:\/\/aaai.org\/Conferences\/AAAI-19\/\">the&nbsp;33rd AAAI&nbsp;Conference&nbsp;on Artificial Intelligence&nbsp;<strong>(AAAI <\/strong>2019)<\/a>,&nbsp;January 27 \u2013 February 1, Honolulu, Hawaii, USA. (Acceptance rate = 1150\/7095&nbsp;=&nbsp;16.2%)&nbsp;[<a href=\"https:\/\/drive.google.com\/file\/d\/1h66G_3YT58Or5rsLU6aZwWeCg9IEXRjx\/view?usp=sharing\">PDF\u200b<\/a>][Bib][<a href=\"https:\/\/drive.google.com\/file\/d\/1KedHlg6bVN5RDv7WAziVw4UlAjKbJd6u\/view?usp=sharing\">Slides<\/a><a href=\"https:\/\/mine.kaust.edu.sa\/Documents\/slides\/kdd2018_embeddings.pdf\">\u200b<\/a>][<a href=\"https:\/\/github.com\/voladorlu\/MARank\">Code<\/a>].\u200b<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Basmah Altaf, Lu Yu,&nbsp;and&nbsp;Xiangliang Zhang: Spatio-Temporal Attention based recurrent neural network for next poi prediction.&nbsp;In proceedings of&nbsp;<a href=\"http:\/\/cci.drexel.edu\/bigdata\/bigdata2018\/index.html\">IEEE Big Data 2018<\/a>,&nbsp;Seattle, WA, USA,&nbsp;December 10-13, 2018 (short paper)[<a href=\"https:\/\/drive.google.com\/file\/d\/1fpk4eIx63cc5bCrK-zm12n69R2bHSUOP\/view?usp=sharing\">PDF<\/a><a href=\"https:\/\/mine.kaust.edu.sa\/Documents\/papers\/walkranker_camera_ID749.pdf\">\u200b<\/a><a href=\"https:\/\/mine.kaust.edu.sa\/Documents\/papers\/wraaaiv5.pdf\">\u200b<\/a>][Bib][Slides<a href=\"https:\/\/mine.kaust.edu.sa\/Documents\/slides\/kdd2018_embeddings.pdf\">\u200b<\/a>].\u200b<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Chuxu Zhang,&nbsp;Lu Yu,&nbsp;Xiangliang Zhang,&nbsp;Nitesh Chawla: Task-Guided and Semantic-Aware Ranking for Academic Author-Paper Correlation Inference.&nbsp;<a href=\"https:\/\/www.ijcai-18.org\/\">27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (<strong>IJCAI<\/strong>&nbsp;2018)\u200b<\/a>, pp.&nbsp;3641-3647,&nbsp;Stockholm, Sweden,&nbsp;July 13-19 2018&nbsp;(acceptance rate= 710\/ 3470 = 20.4%)[<a href=\"https:\/\/drive.google.com\/file\/d\/1IMqtUOajjJrzrvI5sgTdK1LG1xhmUWTJ\/view?usp=sharing\">PDF\u200b<\/a><a href=\"https:\/\/mine.kaust.edu.sa\/Documents\/papers\/walkranker_camera_ID749.pdf\">\u200b<\/a><a href=\"https:\/\/mine.kaust.edu.sa\/Documents\/papers\/wraaaiv5.pdf\">\u200b<\/a>][Bib].\u200b<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Lu Yu, Chuxu Zhang,&nbsp;Shichao Pei,&nbsp;Guolei Sun,&nbsp;Xiangliang Zhang: WalkRanker: A Unified Pairwise Ranking Model with Multiple Relations for Item Recommendation. In Proceedings&nbsp;of&nbsp;<a href=\"https:\/\/aaai.org\/Conferences\/AAAI-18\/\">the 32nd AAAI Conference on Artificial Intelligence (<strong>AAAI <\/strong>2018)<\/a>,&nbsp;pp.&nbsp;2596-2603,&nbsp;New Orleans, February 2\u20137, 2018&nbsp;(acceptance rate= 933\/ 3800 = 24.6%)[PDF<a href=\"https:\/\/mine.kaust.edu.sa\/Documents\/papers\/walkranker_camera_ID749.pdf\">\u200b<\/a><a href=\"https:\/\/mine.kaust.edu.sa\/Documents\/papers\/wraaaiv5.pdf\">\u200b<\/a>][Bib].\u200b<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Chuxu Zhang, Chao Huang,&nbsp;Lu Yu,&nbsp;Xiangliang Zhang,&nbsp;Nitesh Chawla: Camel: Content-Aware and Meta-path Augmented Metric Learning for Author Identification. In Proceedings of&nbsp;the&nbsp;<a href=\"https:\/\/www2018.thewebconf.org\/\">27th International World Wide Web Conference&nbsp;(<strong>WWW <\/strong>2018) (the Web Conference 2018)<\/a>, pp. 709-718,&nbsp;Lyon, France, Apr 23 &#8211; 27, 2018 (acceptance rate = 171\/1155=14.8%)[<a href=\"https:\/\/drive.google.com\/file\/d\/1KWIttA6xkwctWvysEPp66cI_pr3dJ-vs\/view?usp=sharing\">PDF<\/a>][Bib].\u200b<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Fuzhen Zhuang, Jing Zheng, Jingwu Chen,&nbsp;Xiangliang Zhang, Chuan Shi, Qing He. Transfer collaborative filtering from multiple sources via consensus regularization.&nbsp;In&nbsp;<a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S089360801830248X\">Neural Networks&nbsp;<\/a>Volume 108, pp. 287-295, December 2018.<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Chuxu Zhang,&nbsp;Lu Yu,&nbsp;Xiangliang Zhang, Nitesh Chawla:&nbsp;ImWalkMF: Joint Matrix Factorization and Implicit Walk Integrative Learning for Recommendation. In Proceedings of the&nbsp;<a href=\"http:\/\/cci.drexel.edu\/bigdata\/bigdata2017\/\">2017 IEEE International conference on Big Data (IEEE BigData&nbsp;2017)<\/a>,&nbsp;pp.&nbsp;857-866, Boston, December 11-14, 2017 (acceptance rate=79\/437=18%)&nbsp;[<a href=\"https:\/\/drive.google.com\/file\/d\/1uE1gl0-3Ex6XEeAbPk_QYQzL8v2Kn8P_\/view?usp=sharing\">PDF<\/a>][Bib].\u200b<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Uchenna Akujuobi,&nbsp;Xiangliang Zhang: Delve: A Dataset-Driven Scholarly Search and Analysis System. In&nbsp;<a href=\"http:\/\/www.kdd.org\/explorations\/\">SIGKDD Explorations<\/a>,&nbsp; Vol.&nbsp;19, Issue 2, pp. 36-46,&nbsp;2017&nbsp;[<a href=\"https:\/\/drive.google.com\/file\/d\/1zH2FunuCBbdhctLKLy7nbUcj5kmRIQDn\/view?usp=sharing\">PDF\u200b<\/a>][Bib].\u200b<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>&nbsp;Basmah Altaf,&nbsp;Faisal Kamiran,&nbsp;Xiangliang Zhang:&nbsp;Modeling Temporal Behavior of Awards Effect on Viewership of Movies.&nbsp;<a href=\"http:\/\/pakdd2017.snu.ac.kr\/\">The&nbsp;2017&nbsp;Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2017)<\/a>,&nbsp;pp. 724-736,&nbsp;Jeju, South Korea,&nbsp;May 23-26, 2017&nbsp;(acceptance rate = (45+84)\/458=28.2%)&nbsp;[<a href=\"https:\/\/drive.google.com\/file\/d\/1RqRvKEKNudfrtmkxLNRxZEewDHtR_fY9\/view?usp=sharing\">PDF\u200b<\/a>][<a href=\"http:\/\/dblp.uni-trier.de\/rec\/bibtex\/conf\/pakdd\/AltafKZ17\">Bib<\/a>]<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Chuxu Zhang,&nbsp;Lu Yu, Yan Wang, Chirag Shah,&nbsp;Xiangliang Zhang,&nbsp;\u201cCollaborative User Network Embedding for Social Recommender Systems\u201c. In Proceedings of&nbsp;<a href=\"http:\/\/www.siam.org\/meetings\/sdm17\/\">2017 SIAM International Conference on Data Mining (<strong>SDM<\/strong> 2017)\u200b<\/a>, pp.&nbsp;381-389,&nbsp;Houston, Texas, April 27 &#8211; 29, 2017 (acceptance rate = 26%)&nbsp;[PDF][<a href=\"http:\/\/dblp.uni-trier.de\/rec\/bibtex\/conf\/sdm\/ZhangYWSZ17\">Bib<\/a>].<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>We design machine learning based models for session-based recommendation, sequential recommendation, social recommendation, POI recommendation, safe recommendation, interpretable recommendation, and so on.<\/p>\n","protected":false},"author":4036,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-113","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/sites.nd.edu\/xiangliang-zhang\/wp-json\/wp\/v2\/pages\/113","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.nd.edu\/xiangliang-zhang\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.nd.edu\/xiangliang-zhang\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.nd.edu\/xiangliang-zhang\/wp-json\/wp\/v2\/users\/4036"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.nd.edu\/xiangliang-zhang\/wp-json\/wp\/v2\/comments?post=113"}],"version-history":[{"count":21,"href":"https:\/\/sites.nd.edu\/xiangliang-zhang\/wp-json\/wp\/v2\/pages\/113\/revisions"}],"predecessor-version":[{"id":1579,"href":"https:\/\/sites.nd.edu\/xiangliang-zhang\/wp-json\/wp\/v2\/pages\/113\/revisions\/1579"}],"wp:attachment":[{"href":"https:\/\/sites.nd.edu\/xiangliang-zhang\/wp-json\/wp\/v2\/media?parent=113"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}