InterSentiment: Combining deep neural models on interaction and sentiment for review rating prediction

• Main Authors: FENG, Shi, SONG, Kaisong, WANG, Daling, GAO, Wei, ZHANG, Yifei
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Review rating prediction; Deep neural networks; Matrix factorization; Sentiment analysis; User-product interaction; Artificial Intelligence and Robotics; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/5646; https://ink.library.smu.edu.sg/context/sis_research/article/6649/viewcontent/InterSentimentCombiningDeep_2021_av.pdf
• Institution: Singapore Management University

Review rating prediction is commonly approached from the perspective of either Collaborative Filtering (CF) or Sentiment Classification (SC). CF-based approach usually resorts to matrix factorization based on user–item interaction, and does not fully utilize the valuable review text features. In con...