A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words
Joint Authors
Huang, Y.
Wang, Bingkun
Wu, Xian
Li, Xing
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-04-23
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
With the spurt of online user-generated contents on web, sentiment analysis has become a very active research issue in data mining and natural language processing.
As the most important indicator of sentiment, sentiment words which convey positive and negative polarity are quite instrumental for sentiment analysis.
However, most of the existing methods for identifying polarity of sentiment words only consider the positive and negative polarity by the Cantor set, and no attention is paid to the fuzziness of the polarity intensity of sentiment words.
In order to improve the performance, we propose a fuzzy computing model to identify the polarity of Chinese sentiment words in this paper.
There are three major contributions in this paper.
Firstly, we propose a method to compute polarity intensity of sentiment morphemes and sentiment words.
Secondly, we construct a fuzzy sentiment classifier and propose two different methods to compute the parameter of the fuzzy classifier.
Thirdly, we conduct extensive experiments on four sentiment words datasets and three review datasets, and the experimental results indicate that our model performs better than the state-of-the-art methods.
American Psychological Association (APA)
Wang, Bingkun& Huang, Y.& Wu, Xian& Li, Xing. 2015. A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words. Computational Intelligence and Neuroscience،Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1057713
Modern Language Association (MLA)
Wang, Bingkun…[et al.]. A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words. Computational Intelligence and Neuroscience No. 2015 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1057713
American Medical Association (AMA)
Wang, Bingkun& Huang, Y.& Wu, Xian& Li, Xing. A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words. Computational Intelligence and Neuroscience. 2015. Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1057713
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057713