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).
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Keyword(in English) Research mining / Clustering / Maximum Margin Clustering
Paper # DE2011-34
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Committee DE
Conference Date 2011/7/26(1days)
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Registration To Data Engineering (DE)
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
Sub Title (in English)
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
Date of Issue