Beyond the stars
Published 6 November 2009Open access
Niklas Jakob, H. Wéber, Mark-Christoph Müller, Iryna Gurevych
Citations161
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TL;DR
It is shown that the extraction of opinions from free-text reviews can improve the accuracy of movie recommendations and the opinion mining based features perform significantly better than the baseline, which is based on star ratings and genre information only.
Abstract
Many web sites collect reviews of products and services and use them provide rankings of their quality. However, such rankings are not personalized. We investigate how the information in the reviews written by a particular user can be used to personalize the ranking she is shown. We propose a new technique, topic profile collaborative filtering, where we build user profiles from users' review texts and use these profiles to filter other review texts with the eyes of this user. We verify on data from an actual review site that review texts and topic profiles indeed correlate with ratings, and show that topic profile collaborative filtering provides both a better mean average error when predicting ratings and a better approximation of user preference orders.
Keywords
Computer Science
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