Presentation | 2011-08-03 Maximum Margin Clustering of Research Papers Based on Meta Information to Generate Research History MANHCUONG NGUYEN, Taiichi HASHIMOTO, Haruo YOKOTA, |
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Abstract(in English) | Our research aim is an automatic generation of a researcher's research history from research articles published on the internet. The research history generation based on k-Means clustering algorithm is proposed in a previous work. However the performance of k-Means algorithm is dissatisfied with it. We propose a method based on Maximum Margin Clustering(MMC). MMC is a new clustering algorithm based on Support Vector Machine(SVM). It is known that MMC is better than existing clustering algorithm, such as k-Means. In this paper, we describe how to convert articles into vectors by meta information of them and decide initial setting of MMC automatically. We illustrate that purity of a method based on MMC is about 0.67 and entropy is about 0.35 in our experimentations. The results is better than one of previous work (purity: 0.35, entropy: 0.47). |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Research mining / Clustering / Maximum Margin Clustering |
Paper # | DE2011-34 |
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Committee | DE |
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Conference Date | 2011/7/26(1days) |
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Registration To | Data Engineering (DE) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Maximum Margin Clustering of Research Papers Based on Meta Information to Generate Research History |
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Keyword(1) | Research mining |
Keyword(2) | Clustering |
Keyword(3) | Maximum Margin Clustering |
1st Author's Name | MANHCUONG NGUYEN |
1st Author's Affiliation | Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology() |
2nd Author's Name | Taiichi HASHIMOTO |
2nd Author's Affiliation | The Research Project Support Center, Tokyo Institute of Technology |
3rd Author's Name | Haruo YOKOTA |
3rd Author's Affiliation | Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology |
Date | 2011-08-03 |
Paper # | DE2011-34 |
Volume (vol) | vol.111 |
Number (no) | 173 |
Page | pp.pp.- |
#Pages | 6 |
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