Data Clustering Using the Concept of Psychological Potential Field

Yitong ZHANG  Kazuo SHIGETA  Eiji SHIMIZU  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E77-D   No.11   pp.1198-1205
Publication Date: 1994/11/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Issue on Computer Vision)
Category: 
Keyword: 
data clustering,  psychological potential field,  force,  mutual nearest neighbourhood,  crossed clusters,  

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Summary: 
A new approach of data clustering which is capable of detecting linked or crossed clusters, is proposed. In conventional clustering approaches, it is a hard work to separate linked or crossed clusters if the cluster prototypes are difficult to be represented by a mathematical formula. In this paper, we extract the force information from data points using the concept of psychological potential field, and utilize the information to measure the similarity between data points. Through several experiments, the force shows its effectiveness in diiscriminating different clusters even if they are linked or corssed.