For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
Data Clustering Using the Concept of Psychological Potential Field
Yitong ZHANG Kazuo SHIGETA Eiji SHIMIZU
IEICE TRANSACTIONS on Information and Systems
Publication Date: 1994/11/25
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Issue on Computer Vision)
data clustering, psychological potential field, force, mutual nearest neighbourhood, crossed clusters,
Full Text: PDF>>
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.