Serendipitous Recommendation in E-Commerce Using Innovator-Based Collaborative Filtering

Volume: 49, Issue: 7, Pages: 2678 - 2692
Published: Jul 1, 2019
Abstract
Collaborative filtering (CF) algorithms have been widely used to build recommender systems since they have distinguishing capability of sharing collective wisdoms and experiences. However, they may easily fall into the trap of the Matthew effect, which tends to recommend popular items and hence less popular items become increasingly less popular. Under this circumstance, most of the items in the recommendation list are already familiar to users...
Paper Details
Title
Serendipitous Recommendation in E-Commerce Using Innovator-Based Collaborative Filtering
Published Date
Jul 1, 2019
Volume
49
Issue
7
Pages
2678 - 2692
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.