Landscape view of recommender system techniques based on sentiment analysis
Publish Year: 1402
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_IJNAA-14-1_117
تاریخ نمایه سازی: 5 شهریور 1402
Abstract:
Over the last several years, sentiment analysis has emerged as one of the most popular applications of machine learning. It enables the identification of a user's attitude from a remark, document, or review. As a result of the development of Big Data, recommender systems (RS) are also finding more use in many aspects of day-to-day living. There are three basic kinds of RS: collaborative filtering, content-based, and hybrid. This article presents a quick description of the recommender systems supplemented with a sentiment analysis module. Sentiment Analysis systems may help recommender systems improve by assessing Web-based reviews.
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Authors
Rosul Kazem
Department of Computer Science, Collage of Education, University of Kufa, Najaf, Iraq
Enas Abdullah
Department of Computer Science, Collage of Education for Girls, University of Kufa, Najaf, Iraq