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.
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Dong, R., Schaal, M., O’Mahony, M.P., McCarthy, K., Smyth, B. (2013). Opinionated Product Recommendation. In: Delany, S.J., Ontañón, S. (eds) Case-Based Reasoning Research and Development. ICCBR 2013. Lecture Notes in Computer Science(), vol 7969. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39056-2_4
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DOI: https://doi.org/10.1007/978-3-642-39056-2_4
Publisher Name: Springer, Berlin, Heidelberg
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