Research history generation from metainformation of research papers using maximum margin clustering

Authors:
Manh Cuong Nguyen;Daichi Kato;Taiichi Hashimoto;Haruo Yokota
Affiliations:
Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo, Japan;Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo, Japan;Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo, Japan;Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo, Japan
Venue:
International Journal of Business Intelligence and Data Mining
Year:
2012

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Abstract

Recently, analysing research papers to understand research trends researcher's research topics automatically from metainformation of research papers published on the internet. Our method is based on Maximum Margin Clustering (MMC). We describe how to represent research papers in form of vectors using metainformation about them and how to initialise the hyperplane for MMC automatically. In the experiments, we show that the purity of our method is higher than that achieved in previous work based on k-Means (0.58 vs 0.35) and entropy of our method is lower than that of previous work (0.415 vs 0.47). Experiment results also illustrates that keyword information of research papers affects the most to clustering result.