This work is in the general area of opinion extraction or opinion mining, and feature-based opinion summarization. It is also closely related to sentiment classification. Our current work focuses on opinions in customer reviews on the Web. 数据挖掘实验室
It is a common practice that merchants selling products on the Web ask their customers to review the products and associated services. As e-commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. For a popular product, the number of reviews can be in hundreds or even thousands. This makes it difficult for a potential customer to read them to make a decision whether to buy the product. It also makes it difficult for the manufacturer of the product to keep track and manage customer opinions. For the manufacturer, there are additional difficulties because many merchant sites may sell the product and the manufacturer normally produces many kinds of products. In this research, we aim to mine and to summarize all the customer reviews of a product. This summarization task is different from traditional text summarization because we only mine the features of the product on which the customers have expressed their opinions and whether the opinions are positive or negative. We do not summarize the reviews by selecting a subset or rewrite some sentences of the original sentences from the reviews to capture the main points as in the classic text summarization. Our task is performed in three steps: (1) mining product features that have been commented on by customers; (2) identifying opinion sentences in each review and deciding whether each opinion sentence is positive or negative; (3) summarizing the results. We have proposed a few techniques to perform these tasks. Our experimental results using reviews of a number of products sold online demonstrate the effectiveness of these techniques. 数据挖掘研究院
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- Bing Liu, Minqing Hu and Junsheng Cheng. "Opinion Observer: Analyzing and Comparing Opinions on the Web" To appear in Proceedings of the 14th international World Wide Web conference (WWW-2005), May 10-14, 2005, in Chiba, Japan. [PDF]
- Minqing Hu and Bing Liu. "Mining and summarizing customer reviews". Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD-2004, full paper), Seattle, Washington, USA, Aug 22-25, 2004. [PDF]
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- Minqing Hu and Bing Liu. "Mining Opinion Features in Customer Reviews." Proceedings of Nineteeth National Conference on Artificial Intellgience (AAAI-2004), San Jose, USA, July 2004. [PDF]
Here is the data Customer Review Datasets associated with papers 3 and 4 above. The dataset used in papers 1 and 2 will be released soon.
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