DocumentCode
1868251
Title
Specialized Review Selection for Feature Rating Estimation
Author
Long, Chong ; Zhang, Jie ; Huang, Minlie ; Zhu, Xiaoyan ; Li, Ming ; Ma, Bin
Volume
1
fYear
2009
fDate
15-18 Sept. 2009
Firstpage
214
Lastpage
221
Abstract
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
Computer science; Conferences; Costs; Data mining; Information science; Intelligent agent; Intelligent systems; Recommender systems; State estimation; Text mining; Data Mining; Information Distance; Kolmogorov Complexity; Text Mining;
fLanguage
English
Publisher
iet
Conference_Titel
Web Intelligence and Intelligent Agent Technologies, 2009. WI-IAT '09. IEEE/WIC/ACM International Joint Conferences on
Conference_Location
Milan, Italy
Print_ISBN
978-0-7695-3801-3
Electronic_ISBN
978-1-4244-5331-3
Type
conf
DOI
10.1109/WI-IAT.2009.38
Filename
5286073
Link To Document