An efficient MDS algorithm for the analysis of massive document collections

Authors:
Yoshitatsu Matsuda;Kazunori Yamaguchi
Affiliations:
Kazunori Yamaguchi Laboratory, Department of General Systems Studies, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan;Kazunori Yamaguchi Laboratory, Department of General Systems Studies, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
Venue:
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Year:
2005

Citing 3
Cited 0

Original Contribution: Principal components, minor components, and linear neural networks

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An efficient MDS-based topographic mapping algorithm

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Self organization of a massive document collection

IEEE Transactions on Neural Networks

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Abstract

In order to solve multidimensional scaling (MDS) efficiently, we proposed an algorithm, which apply stochastic gradient algorithm to minimizing well-known MDS criteria [1]. In this paper, the efficient MDS algorithm is applied to the text mining and compared with the SOM [2]. The results verified the validity of our algorithm in the analysis of a massive document collection. Our algorithm could find out some interesting structures from about 100000 articles in Usenet (NetNews).