Jointly Modeling Aspects, Ratings and Sentiments for Movie Recommendation (JMARS)

• Main Authors: DIAO, Qiming, QIU, Minghui, WU, Chao-Yuan, SMOLA, Alexander J., JIANG, Jing, WANG, Chong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2014
• Subjects: Collaborative Filtering; Topic Models; Integrated Modeling; Sentiment Analysis; Computer Sciences; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/2415; https://ink.library.smu.edu.sg/context/sis_research/article/3415/viewcontent/jmars_kdd2014.pdf
• Institution: Singapore Management University

Recommendation and review sites offer a wealth of information beyond ratings. For instance, on IMDb users leave reviews, commenting on different aspects of a movie (e.g. actors, plot, visual effects), and expressing their sentiments (positive or negative) on these aspects in their reviews. This sugg...