Mining Experiential Product Cases
Refereed Conference Meeting Proceeding
Case-based reasoning (CBR) attempts to reuse past expe- riences to solve new problems. CBR ideas are commonplace in recom- mendation systems, which rely on the similarity between product queries and a case base of product cases . But, the relationship between CBR and many of these recommenders can be tenuous: the idea that prod- uct cases made up of static meta-data type features are experiential is a stretch; unless one views the type of case descriptions used by collab- orative ltering (user ratings across products) as experiential. Here we explore and evaluate how to automatically generate product cases from user-generated reviews to produce cases that are based on genuine user experiences for use in a case-based product recommendation system.
Digital Object Identifer (DOI):
United States of America
National University of Ireland, Dublin (UCD)
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