Landscape view of recommender system techniques based on sentiment analysis

	Landscape view of recommender system techniques based on sentiment analysis
International Journal of Nonlinear Analysis and Applications
مقاله 117، دوره 14، شماره 1، فروردین 2023، صفحه 1539-1546 اصل مقاله (437.19 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.7138
نویسندگان
Rosul Ibrahim Kazem¹؛ Enas Fadhil Abdullah^* ²
¹Department of Computer Science, Collage of Education, University of Kufa, Najaf, Iraq
²Department of Computer Science, Collage of Education for Girls, University of Kufa, Najaf, Iraq
چکیده
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.
کلیدواژه‌ها
recommender systems؛ contextual meaning؛ sentiment analysis
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