Recommendations Using Information from Multiple Association Rules: A Probabilistic Approach

Volume: 26, Issue: 3, Pages: 532 - 551
Published: Sep 1, 2015
Abstract
Business analytics has evolved from being a novelty used by a select few to an accepted facet of conducting business. Recommender systems form a critical component of the business analytics toolkit and, by enabling firms to effectively target customers with products and services, are helping alter the e-commerce landscape. A variety of methods exist for providing recommendations, with collaborative filtering, matrix factorization, and...
Paper Details
Title
Recommendations Using Information from Multiple Association Rules: A Probabilistic Approach
Published Date
Sep 1, 2015
Volume
26
Issue
3
Pages
532 - 551
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.