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

Alia Karim Abdul Hassan --- Ahmed Bahaa Aldeen Abdulwahhab

Iraqi Journal of Science المجلة العراقية للعلوم
ISSN: 00672904/23121637 Year: 2018 Volume: 59 Issue: 2A Pages: 771-785
Publisher: Baghdad University جامعة بغداد


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.