Opinionated Product Recommendation [chapter]

Ruihai Dong, Markus Schaal, Michael P. O'Mahony, Kevin McCarthy, Barry Smyth
2013 Lecture Notes in Computer Science  
In this paper we describe a novel approach to case-based product recommendation. It is novel because it does not leverage the usual static, feature-based, purely similarity-driven approaches of traditional case-based recommenders. Instead we harness experiential cases, which are automatically mined from user generated reviews, and we use these as the basis for a form of recommendation that emphasises similarity and sentiment. We test our approach in a realistic product recommendation setting by using live-product data and user reviews.
doi:10.1007/978-3-642-39056-2_4 fatcat:azjfhgspsfcbxfulx6sk5xxmzm