{"id":2644,"date":"2023-02-21T13:43:27","date_gmt":"2023-02-21T13:43:27","guid":{"rendered":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/speakers\/walt-degrange-copy\/"},"modified":"2023-02-21T13:59:24","modified_gmt":"2023-02-21T13:59:24","slug":"yong-zheng","status":"publish","type":"page","link":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/speakers\/yong-zheng\/","title":{"rendered":"Yong Zheng"},"content":{"rendered":"\n
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\n Yong Zheng <\/h3>\n <\/div>\n \n <\/div>\n <\/div>\n
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Yong Zheng<\/h1>\n

Assistant Professor at Illinois Institute of Technology<\/span><\/h1>\n
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Dr. Yong Zheng is a tenure-track Assistant Professor at Illinois Institute of Technology, Chicago, USA. He received the PhD degree in computer and information sciences from DePaul University, USA in 2016. He is a leading research in recommender systems. His research interests lie in decision making, user modeling, personalization and recommender systems, and particularly, he devoted the efforts in bringing decision making theories (e.g., group decisions, multi-criteria decision making, multi-objective optimization, etc. ) into the practice of recommender systems. He has been actively engaged in the organization committee of the conferences related to the area of recommender systems, including ACM RecSys (2018, 2023), ACM UMAP (2018 – 2022), ACM Hypertext (2022) and ACM IUI (2018, 2019, 2021, 2023).<\/p>\n<\/div> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Track: Behavioral Analytics<\/h6> <\/div>\n<\/div>\n\n
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Multi-Criteria Ranking for Recommender Systems<\/h2>\n

Recommender Systems have been served in multiple areas (e.g., e-commerce, hotel bookings, job seeking, social media, online streaming, etc.) to assist users’ decision making. Multi-Criteria Recommender Systems (MCRS) are a special type of recommender systems, where the system can produce item recommendations by taking advantage of user preferences on different aspects of the items (i.e., criteria). Apparently, there is a process of multi-criteria decision making involved. However, the development of MCRS algorithms failed to fill the gap between multi-criteria decision making and recommender systems. Most of the MCRS algorithms simply utilized an aggregation function (e.g., weighted sum) to estimate the overall preference by a user on an item. In this talk, we discuss our recent and promising technique, multi-criteria ranking, which reuses the knowledge and techniques in multi-criteria decision making and multi-objective optimization to boost the performance of multi-criteria recommender systems, in order to deliver more accurate item recommendations.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n","protected":false},"excerpt":{"rendered":"

Yong Zheng Yong Zheng Assistant Professor at Illinois Institute of Technology Dr. Yong Zheng is a tenure-track Assistant Professor at Illinois Institute of Technology, Chicago, USA. He received the PhD degree in computer and information sciences from DePaul University, USA in 2016. He is a leading research in recommender systems. His research interests lie in […]<\/p>\n","protected":false},"author":1001094,"featured_media":2647,"parent":712,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"class_list":["post-2644","page","type-page","status-publish","has-post-thumbnail","hentry","has-post-title","has-post-date","has-post-category","has-post-tag","has-post-comment","has-post-author",""],"acf":[],"yoast_head":"\nYong Zheng - 2023 INFORMS Business Analytics Conference<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/speakers\/yong-zheng\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Yong Zheng\" \/>\n<meta property=\"og:description\" content=\"Yong Zheng Yong Zheng Assistant Professor at Illinois Institute of Technology Dr. Yong Zheng is a tenure-track Assistant Professor at Illinois Institute of Technology, Chicago, USA. 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He received the PhD degree in computer and information sciences from DePaul University, USA in 2016. He is a leading research in recommender systems. His research interests lie in decision making, user modeling, personalization and recommender systems, and particularly, he devoted the efforts in bringing decision making theories (e.g., group decisions, multi-criteria decision making, multi-objective optimization, etc. ) into the practice of recommender systems. He has been actively engaged in the organization committee of the conferences related to the area of recommender systems, including ACM RecSys (2018, 2023), ACM UMAP (2018 - 2022), ACM Hypertext (2022) and ACM IUI (2018, 2019, 2021, 2023).<\/p>\n<h6>Track: Behavioral Analytics<\/h6>\n<h2>Multi-Criteria Ranking for Recommender Systems<\/h2> <p>Recommender Systems have been served in multiple areas (e.g., e-commerce, hotel bookings, job seeking, social media, online streaming, etc.) to assist users' decision making. 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