M
Ming-Feng Tsai
Researcher at National Chengchi University
Publications - 111
Citations - 4352
Ming-Feng Tsai is an academic researcher from National Chengchi University. The author has contributed to research in topics: Ranking (information retrieval) & Recommender system. The author has an hindex of 21, co-authored 90 publications receiving 3501 citations. Previous affiliations of Ming-Feng Tsai include University of Missouri & National Taiwan University.
Papers
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Book ChapterDOI
CPR: Cross-Domain Preference Ranking with User Transformation
Yu-Ting Huang,Hsien-Hao Chen,Tung-Lin Wu,Chia-Yu Yeh,Jing-Kai Lou,Ming-Feng Tsai,Chuan-Ju Wang +6 more
TL;DR: CPR as discussed by the authors leverages user interactions with items in the source and target domains to transform the user representation, which not only enhances recommendation performance for users having interactions with target-domain items but also yields superior performance for cold-start users in comparison with state-of-the-art cross-domain recommendation approaches.
Journal ArticleDOI
Deep Learning-Based Clinical Wound Image Analysis Using a Mask R-CNN Architecture
Shu-Tien Huang,Liong Rung Liu,Wen-Teng Yao,Yu-Fan Chen,Chieh-Ming Yu,Chia-Meng Yu,Kwang Yi Tung,Hung Wen Chiu,Ming-Feng Tsai +8 more
Proceedings ArticleDOI
Ipr
TL;DR: This article proposed interaction-level preference ranking (IPR), a novel pairwise ranking embedding learning approach to better utilize explicit feedback for recommendation, which showed that IPR yields the best results compared to six strong baselines.
Journal ArticleDOI
Safety and Efficacy of Submuscular Implantation With Resterilized Cardiac Implantable Electronic Device in Patients With Device Infection: A Retrospective Observational Study in Taiwan
Chia-Meng Yu,Chieh-Ming Yu,Wen-Teng Yao,Ying Hsiang Lee,Feng-Ching Liao,Chih Yin Chien,Shun-Hsung Chang,Hung Wei Liao,Yu-Fan Chen,Wen-Chen Huang,Kwang Yi Tung,Ming-Feng Tsai +11 more
TL;DR: Subpectoral reimplanting of resterilized CIEDs in patients with previous device infection is safe and efficacious and with delicate debridement and complete extraction of the leads, the CIED pocket infection relapse risk can be greatly decreased.
Proceedings ArticleDOI
RecDelta
TL;DR: RecDelta as mentioned in this paper is a web-based information system where people can visually compare the performance of various recommendation algorithms and their recommended items, and then select the desired user to present the relationship between recommended items and his/her historical behavior.