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Integrating User Reviews and Ratings for Enhanced Personalized Searching

Integrating User Reviews and Ratings for Enhanced Personalized Searching

Shuyue Hu, Yi Cai, Ho-fung Leung, Dongping Huang, Yang Yang
Copyright: © 2017 |Volume: 15 |Issue: 2 |Pages: 16
ISSN: 1539-3100|EISSN: 1539-3119|EISBN13: 9781522511083|DOI: 10.4018/IJDET.2017040106
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MLA

Hu, Shuyue, et al. "Integrating User Reviews and Ratings for Enhanced Personalized Searching." IJDET vol.15, no.2 2017: pp.86-101. http://doi.org/10.4018/IJDET.2017040106

APA

Hu, S., Cai, Y., Leung, H., Huang, D., & Yang, Y. (2017). Integrating User Reviews and Ratings for Enhanced Personalized Searching. International Journal of Distance Education Technologies (IJDET), 15(2), 86-101. http://doi.org/10.4018/IJDET.2017040106

Chicago

Hu, Shuyue, et al. "Integrating User Reviews and Ratings for Enhanced Personalized Searching," International Journal of Distance Education Technologies (IJDET) 15, no.2: 86-101. http://doi.org/10.4018/IJDET.2017040106

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Abstract

With 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.

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