DocumentCode
1812002
Title
Research of Similarity Measurements in the Clustering Analysis
Author
Li, LiuBai ; Hongyao, Deng
Author_Institution
Coll. of Math. & Comput. Sci., Yangtze Normal Univ., Chongqing, China
fYear
2010
fDate
24-25 July 2010
Firstpage
3
Lastpage
6
Abstract
Similarity measurements play an important role in the clustering analysis, so any good or bad methods of measuring similar degree directly affect the clustering algorithm. In the paper, several approaches to similarity measurements for single attribute type data, which had been proposed, have been discussed. Moreover, a way has been obtained so as to calculate the similar degree of multiple attribute type data. At last a experiment was tested. The result shows that the method is not only feasible but also effective.
Keywords
pattern clustering; clustering analysis; multiple attribute type data; similar degree measurement; similarity measurement; single attribute type data; Algorithm design and analysis; Clustering algorithms; Correlation; Equations; Euclidean distance; Mathematical model; White blood cells; attribute type; clustering; distance andcoefficient; similarity measurements;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology and Computer Science (ITCS), 2010 Second International Conference on
Conference_Location
Kiev
Print_ISBN
978-1-4244-7293-2
Electronic_ISBN
978-1-4244-7294-9
Type
conf
DOI
10.1109/ITCS.2010.9
Filename
5557341
Link To Document