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Opinionated Product Recommendation
[chapter]
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