論文

査読有り
2012年

Visualizing cluster structures and their changes over time by two-step application of self-organizing maps

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
  • Masahiro Ishikawa

7104
開始ページ
160
終了ページ
170
記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1007/978-3-642-28320-8_14
出版者・発行元
Springer

In this paper, a novel method for visualizing cluster structures and their changes over time is proposed. Clustering is achieved by two-step application of self-organizing maps (SOMs). By two-step application of SOMs, each cluster is assigned an angle and a color. Similar clusters are assigned similar ones. By using colors and angles, cluster structures are visualized in several fashions. In those visualizations, it is easy to identify similar clusters and to see degrees of cluster separations. Thus, we can visually decide whether some clusters should be grouped or separated. Colors and angles are also used to make clusters in multiple datasets from different time periods comparable. Even if they belong to different periods, similar clusters are assigned similar colors and angles, thus it is easy to recognize that which cluster has grown or which one has diminished in time. As an example, the proposed method is applied to a collection of Japanese news articles. Experimental results show that the proposed method can clearly visualize cluster structures and their changes over time, even when multiple datasets from different time periods are concerned. © 2012 Springer-Verlag.

リンク情報
DOI
https://doi.org/10.1007/978-3-642-28320-8_14
DBLP
https://dblp.uni-trier.de/rec/conf/pakdd/Ishikawa11
URL
http://dblp.uni-trier.de/db/conf/pakdd/pakdd2011-w.html#conf/pakdd/Ishikawa11
ID情報
  • DOI : 10.1007/978-3-642-28320-8_14
  • ISSN : 0302-9743
  • ISSN : 1611-3349
  • DBLP ID : conf/pakdd/Ishikawa11
  • SCOPUS ID : 84857692670

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