TPR: Text-aware Preference Ranking for recommender systems

• Main Authors: CHUANG, Yu-Neng, CHEN, Chih-Ming, WANG, Chuan-Ju, TSAI, Ming-Feng, FANG, Yuan, LIM, Ee-peng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: recommender systems; textual information; preference ranking; Databases and Information Systems; Systems Architecture
• Online Access: https://ink.library.smu.edu.sg/sis_research/5295; https://ink.library.smu.edu.sg/context/sis_research/article/6298/viewcontent/CIKM20_TPR.pdf
• Institution: Singapore Management University

Textual data is common and informative auxiliary information for recommender systems. Most prior art utilizes text for rating prediction, but rare work connects it to top-N recommendation. Moreover, although advanced recommendation models capable of incorporating auxiliary information have been deve...