| Presentation | 2012-08-02 Semi-supervised Sentiment Classification in Resource-Scarce Language : A Comparative Study Yong Ren, Nobuhiro Kaji, Naoki Yoshinaga, Masashi Toyoda, Masaru Kitsuregawa, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | With the advent of consumer generated media (e.g., Amazon reviews, Twitter, etc.), sentiment classification becomes a heated topic. Conventional approaches heavily rely on a large amount of linguistic resources, which are difficult to obtain in resource-scarce languages. To overcome this problem, semi-supervised learning (SSL) algorithms have been exploited. However, for the development and variety involved in SSL literature, when people try to adopt SSL approach in practice, they usually confront difficulty in deciding the proper method from many potential candidates. In this study, we conduct empirical evaluation on several representative SSL algorithms in a document-level sentiment classification task for resource-scarce languages (Chinese in our case), and the comparative experiment is carried out using three real datasets. We will describe corresponding theorems, show characteristics and related existing issues for each evaluated algorithm. We believe the other people who interested in exploiting SSL methods could benefit from our experience. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | sentiment classification / semi-supervised learning / comparative study |
| Paper # | DE2012-26 |
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| Conference Information | |
| Committee | DE |
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| Conference Date | 2012/7/25(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Data Engineering (DE) |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Semi-supervised Sentiment Classification in Resource-Scarce Language : A Comparative Study |
| Sub Title (in English) | |
| Keyword(1) | sentiment classification |
| Keyword(2) | semi-supervised learning |
| Keyword(3) | comparative study |
| 1st Author's Name | Yong Ren |
| 1st Author's Affiliation | Graduate School of Information Science and Technology, The University of Tokyo() |
| 2nd Author's Name | Nobuhiro Kaji |
| 2nd Author's Affiliation | Institute of Industrial Science, The University of Tokyo |
| 3rd Author's Name | Naoki Yoshinaga |
| 3rd Author's Affiliation | Institute of Industrial Science, The University of Tokyo |
| 4th Author's Name | Masashi Toyoda |
| 4th Author's Affiliation | Institute of Industrial Science, The University of Tokyo |
| 5th Author's Name | Masaru Kitsuregawa |
| 5th Author's Affiliation | Institute of Industrial Science, The University of Tokyo |
| Date | 2012-08-02 |
| Paper # | DE2012-26 |
| Volume (vol) | vol.112 |
| Number (no) | 172 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |