Articles

 

Mining Reviews for Product Comparison and Recommendation

 

Jianshu Sun, Chong Long, Xiaoyan Zhu, and Minlie Huang

 

State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China. (e–mail: bigtree2005@gmail.com, longc05@mails.tsinghua.edu.cn, zxy–dcs@tsinghua.edu.cn, aihuang@tsinghua.edu.cn).

 

Manuscript received November 5, 2008.
Manuscript accepted for publication February 19, 2009.

 

Abstract

Recently, as the amount of customer reviews grows rapidly on product service websites, it costs customers much time to select and compare their favorite products. Researchers have been aware of this problem and many studies are investigated to mine the opinions from the online reviews. Unfortunately, few previous works give comparisons or recommendations among the products. In this paper, we propose an automated system to address this problem. We first build a product feature sentiment database from the reviews. Then we perform the comparison among various products from both subjective and objective perspectives on the feature level. Finally, product recommendations can be suggested according to the previous comparisons and an evolution tree constructed from the reviews. Experiment results demonstrate the effectiveness of the proposed approach in mining the digital camera reviews. And now a demo system is put in to practical use.

Key words: Review mining, comparison, recommendation, evolution tree.

 

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ACKNOWLEDGMENT

The work was supported by NSFC under grant No.60621062 and 60803075, the National Basic Research Program (973 project in China) under grant No.2007CB311003, and Microsoft joint project "Opinion Summarization toward Opinion Search". The work was also supported by a grant from the International Development Research Center, Canada.

 

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