Hidden Sentiment Association in Chinese Web Opinion Mining
The boom of product review websites, blogs and forums on the web has attracted many research e.orts on opinion mining. Recently, there was a growing interest in the.nergrained opinion mining, which detects opinions on di.erent review features as opposed to the whole review level. The researches on feature-level opinion mining mainly rely on identifying the explicit relatedness between product feature words and opinion words in reviews. However, the sentiment relatedness between the two objects is usually complicated. For many cases, product feature words are implied by the opinion words in reviews. The detection of such hidden sentiment association is still a big challenge in opinion mining. Especially, it is an even harder task of feature-level opinion mining on Chinese reviews due to the nature of Chinese language. In this paper, we propose a novel mutual reinforcement approach to deal with the feature-level opinion mining problem. More specially, 1) the approach clusters product features and opinion words simultaneously and iteratively by fusing both their content information and sentiment link information. 2) under the same framework, based on the product feature categories and opinion word groups, we construct the sentiment association set between the two groups of data objects by identifying their strongest n sentiment links. Moreover, knowledge from multi-source is incorporated to enhance clustering in the procedure. Based on the pre-constructed association set, our approach can largely predict opinions relating to di.erent product features, even for the case without the explicit appearance of product feature words in reviews. Thus it provides a more accurate opinion evaluation. The experimental results demonstrate that our method outperforms the state-of-art algorithms.
opinion mining product feature opinion word association mutual reinforcement
Qi Su Xinying Xu Honglei Guo Zhili Guo XianWu Xiaoxun Zhang Bin Swen Zhong Su
Peking University Beijing, 100871, China IBM China Research Lab Beijing, 100094, China
国际会议
第十七届国际万维网大会(the 17th International World Wide Web Conference)(WWW08)
北京
英文
2008-04-21（万方平台首次上网日期，不代表论文的发表时间）