Integrating User Reviews and Ratings for Enhanced Personalized Searching
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AbstractWith the development of e-commerce, websites such as Amazon and eBay have become very popular. Users post reviews of products and rate the helpfulness of reviews on these websites. Reviews written by a user and reviews rated by a user reflect the user's interests and disinterest. Thus, they are very useful for user profiling. In this study, the authors explore users' reviews and ratings of reviews for personalized searching and propose a review-based user profiling method. To satisfy a user's basic information needs, expressed in the form of a query, they also propose a priority-based result ranking strategy. For evaluation, they conduct experiments on a real-life data set. The experimental results show that their method can significantly improve retrieval quality.
All Author(s) ListShuyue Hu, Yi Cai, Ho-fung Leung, Dongping Huang, Yang Yang
Journal nameInternational Journal of Distance Education Technologies
Year2017
Month4
Volume Number15
Issue Number2
Pages86 - 101
ISSN1539-3100
eISSN1539-3119
LanguagesEnglish-United States
KeywordsPersonalized Search, Priority-based Ranking, Resource Profiling, User Modeling User Profiling

Last updated on 2020-15-08 at 02:47