The Proposed Collaborative Filtering Recommender System Based on Implicit and Explicit User's Preferences

  • Alia Karim Abdul Hassan Department of Computer science, University of Technology, Baghdad, Iraq.
  • Ahmed Bahaa Aldeen Abdulwahhab Department of Informatics, Middle Technical University, Baghdad, Iraq.
Keywords: recommender system, collaborative filtering, sentiment analysis, implicit feedback

Abstract

The expansion of web applications like e-commerce and other services yields an exponential increase in offers and choices in the web. From these needs, the recommender system applications have arisen. This research proposed a recommender system that uses user's reviews as implicit feedback to extract user preferences from their reviews to enhance personalization in addition to the explicit ratings. Diversity also improved by using k-furthest neighbor algorithm upon user's clusters. The system tested using Douban movie standard dataset from Kaggle, and show good performance. 

Published
2018-04-29
How to Cite
Abdul HassanA. K., & AbdulwahhabA. B. A. (2018). The Proposed Collaborative Filtering Recommender System Based on Implicit and Explicit User’s Preferences. Iraqi Journal of Science, 59(2A), 771-785. Retrieved from http://scbaghdad.edu.iq/eijs/index.php/eijs/article/view/282
Section
Computer Science