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2009
Springer

Specialized Review Selection for Feature Rating Estimation

11 years 8 months ago
Specialized Review Selection for Feature Rating Estimation
—On participatory Websites, users provide opinions about products, with both overall ratings and textual reviews. In this paper, we propose an approach to accurately estimate feature ratings of the products. This approach selects user reviews that extensively discuss specific features of the products (called specialized reviews), using information distance of reviews on the features. Experiments on real data show that overall ratings of the specialized reviews can be used to represent their feature ratings. The average of these overall ratings can be used by recommender systems to provide feature specific recommendations that better help users make purchasing decisions. Keywords-Data Mining; Text Mining; Kolmogorov Complexity; Information Distance
Chong Long, Jie Zhang, Minlie Huang, Xiaoyan Zhu,
Added 25 May 2010
Updated 25 May 2010
Type Conference
Year 2009
Where WEBI
Authors Chong Long, Jie Zhang, Minlie Huang, Xiaoyan Zhu, Ming Li, Bin Ma
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