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Presentations

Chinese Papers 7: Data Mining & Analysis
Time: 25/Mar/2017: 10:30am-12:00pm · Location: Hanyang Hall

Latent Topic Model based Review Opinion Clustering and Measurement

Hui Nie

Sun Yat-sen University, China, People's Republic of

With the rapid growth of internet, a wealth of user-generated product reviews has been spread to the web. However,product reviews posted at commercial websites vary greatly in quality. In the paper, we attempt to solve the problem of how to extract and integrate the useful content from the massive product reviews, in order to make the most of online reviews useful for commercial application. For the purpose, great attention has been focus on the review summation for Chinese language. The two crucial problems for the review summation are the user-opinion based product aspect clustering and the user-opinion measurement. Opinion_LDA, a Latent Aspect Model based on feature words sequence, has been built to aggregate users’ opinion automatically. Meanwhile, a polarity lexicon and modified relations between terms have been employed for measuring the user opinion. The proposed model and method have been tested in a real tablet compute -specific reviews dataset. The result indicates the effectiveness and feasibility of the method for our review summarization task.

 
 
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