Review of Entity Information Type in Recommendation Systems

Authors

  • Jehan Kadhim Shareef Al-safi University of Thi-Qar, Department of Digital Media, Media faculty, 64001, Iraq Author
  • Wijdan Rashid Abdulhussien University of Thi-Qar, Department of Information Technology, Faculty of Computer Science and Mathematics, 64001, Iraq Author
  • Wasan M. Jwaid University of Thi-Qar, Department of Banking and Finance, Faculty of Administration and Economics, 64001, Iraq Author

Keywords:

Collaborative Filtering, Content-based, Item-base CF, User-based CF, User review

Abstract

Users share their opinions on various products through online reviews on e-commerce sites and linked microblogs. Reviews from users are a terrific way to learn more about what kinds of things interest them. Some recent efforts have turned to reviewing texts and the abundance of information they provide to improve overall score collaborative filtering recommender systems. This paper includes review terms, review topics, and review attitudes. The works in question utilize review texts to infer user preferences. In this study, we comprehensively analyze current attempts that use review texts. We investigate how these texts are used to overcome some of the most pressing issues plaguing conventional forms of collaborative filtering.

 

Author Biographies

  • Wijdan Rashid Abdulhussien, University of Thi-Qar, Department of Information Technology, Faculty of Computer Science and Mathematics, 64001, Iraq

     

  • Wasan M. Jwaid, University of Thi-Qar, Department of Banking and Finance, Faculty of Administration and Economics, 64001, Iraq

     

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Published

2025-05-01

Issue

Vol. 4 No. 1 (2025)

Section

Articles