2021/09/18 by Sumaia Mohammed Al-Ghuribi, AL-Ghuribi, Sumaia Mohammed, Shahrul Azman Mohd Noah +1 · 1 citation
Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Recommender Systems and Techniques #Sentiment Analysis and Opinion Mining #Text and Document Classification Technologies
paper · pdf · doi:10.48550/arxiv.2109.08794
openalex publication_date 2021/09/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Recommender system has been proven to be significantly crucial in many fields and is widely used by various domains. Most of the conventional recommender systems rely on the numeric rating given by a user to reflect his opinion about a consumed item; however, these ratings are not available in many domains. As a result, a new source of information represented by the user-generated reviews is incorporated in the recommendation process to compensate for the lack of these ratings. The reviews contain prosperous and numerous information related to the whole item or a specific feature that can be extracted using the sentiment analysis field. This paper gives a comprehensive overview to help researchers who aim to work with recommender system and sentiment analysis. It includes a background of the recommender system concept, including phases, approaches, and performance metrics used in recommender systems. Then, it discusses the sentiment analysis concept and highlights the main points in the sentiment analysis, including level, approaches, and focuses on aspect-based sentiment analysis.