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.

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
Apr 29, 2018
How to Cite
ABDUL HASSAN, Alia Karim; ABDULWAHHAB, Ahmed Bahaa Aldeen. Proposed Collaborative Filtering Recommender System Based on Implicit and Explicit User's Preferences. Iraqi Journal of Science, [S.l.], p. 771-785, apr. 2018. ISSN 2312-1637. Available at: <http://scbaghdad.edu.iq/eijs/index.php/eijs/article/view/282>. Date accessed: 26 may 2018.
Section
Computer Science