Integrating User Reviews and Ratings for Enhanced Personalized Searching

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...

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Bibliographic Details
Published in:International journal of distance education technologies 2017-04, Vol.15 (2), p.86-101
Main Authors: Hu, Shuyue, Cai, Yi, Leung, Ho-fung, Huang, Dongping, Yang, Yang
Format: Article
Language:English
Subjects:
Customization
Distance education
Distance learning
Education
Electronic commerce
Information Needs
Information Retrieval
Internet
Keywords
Personalized
Profiling
Query expansion
Ratings
Ratings & rankings
Search Engines
Searching
Software engineering
Strategy
Student Interests
User profiles
User Satisfaction (Information)
Users (Information)
Web Sites
Websites
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Summary: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.
ISSN:1539-3100
1539-3119
DOI:10.4018/IJDET.2017040106