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2010
ACM

Latent aspect rating analysis on review text data: a rating regression approach

9 years 2 months ago
Latent aspect rating analysis on review text data: a rating regression approach
In this paper, we define and study a new opinionated text data analysis problem called Latent Aspect Rating Analysis (LARA), which aims at analyzing opinions expressed about an entity in an online review at the level of topical aspects to discover each individual reviewer’s latent opinion on each aspect as well as the relative emphasis on different aspects when forming the overall judgment of the entity. We propose a novel probabilistic rating regression model to solve this new text mining problem in a general way. Empirical experiments on a hotel review data set show that the proposed latent rating regression model can effectively solve the problem of LARA, and that the detailed analysis of opinions at the level of topical aspects enabled by the proposed model can support a wide range of application tasks, such as aspect opinion summarization, entity ranking based on aspect ratings, and analysis of reviewers rating behavior. Categories and Subject Descriptors H.3.3 [Information ...
Hongning Wang, Yue Lu, Chengxiang Zhai
Added 29 Jan 2011
Updated 29 Jan 2011
Type Journal
Year 2010
Where KDD
Authors Hongning Wang, Yue Lu, Chengxiang Zhai
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