Opinionated Product Recommendation
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|Title:||Opinionated Product Recommendation||Authors:||Dong, Ruihai
O'Mahony, Michael P.
|Permanent link:||http://hdl.handle.net/10197/8314||Date:||11-Jul-2013||Abstract:||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.||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||Springer||Keywords:||Recommender systems;Experience web||DOI:||10.1007/978-3-642-39056-2_4||Language:||en||Status of Item:||Peer reviewed||Is part of:||Delany, S.J. and Ontanon, S. (eds.). Proceedings 21st International Conference (ICCBR 2013) (Lecture Notes in Computer Science Volume 7969)||Conference Details:||21st International Conference (ICCBR 2013), Saratoga Springs, New York, USA, 8-11 July 2013|
|Appears in Collections:||CLARITY Research Collection|
Computer Science Research Collection
Insight Research Collection
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