Categorical data visualization and clustering using subjective factors

Chia Hui Chang, Zhi Kai Ding

研究成果: 書貢獻/報告類型篇章同行評審

2 引文 斯高帕斯(Scopus)

摘要

A common issue in cluster analysis is that there is no single correct answer to the number of clusters, since cluster analysis involves human subjective judgement. Interactive visualization is one of the methods where users can decide a proper clustering parameters. In this paper, a new clustering approach called CDCS (Categorical Data Clustering with Subjective factors) is introduced, where a visualization tool for clustered categorical data is developed such that the result of adjusting parameters is instantly reflected. The experiment shows that CDCS generates high quality clusters compared to other typical algorithms.

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主出版物標題Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
編輯Yahiko Kambayashi, Mukesh Mohania, Wolfram Wöß
發行者Springer Verlag
頁面229-238
頁數10
ISBN(列印)354022937X, 9783540229377
DOIs
出版狀態已出版 - 2004

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
3181
ISSN(列印)0302-9743
ISSN(電子)1611-3349

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