Factor Controlled Hierarchical SOM Visualization for Large Set of Data(Special Issue on Text Processing for Information Access)

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概要

• 論文の詳細を見る

• Self-organizing map is a widely used tool in high-dimensional data visualization. However, despite its benefits of plotting very high-dimensional data on a low-dimensional grid, browsing and understanding the meaning of a trained map turn to be a difficult task - specially when number of nodes or the size of data increases. Though there are some well-known techniques to visualize SOMs, they mainly deals with cluster boundaries and they fail to consider raw information available in original data in browsing SOMs. In this paper, we propose our Factor controlled Hierarchical SOM that enables us select number of data to train and label a particular map based on a pre-defined factor and provides consistent hierarchical SOM browsing.

• 一般社団法人電子情報通信学会の論文
• 2003-09-01

著者

• Umemura Kyoji

  Dept. Of Information And Computer Sciences Toyohashi University

• Umemura Kyoji

  Dept. Of Computer Science And Eng. Toyohashi University Of Tech.

• CHAKMA Junan

  Dept. of Information and Computer Sciences, Toyohashi University

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• Factor Controlled Hierarchical SOM Visualization for Large Set of Data(Special Issue on Text Processing for Information Access)
• Analytical Modeling of Network Throughput Prediction on the Internet

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