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
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;
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
DOI :
10.1109/ITCS.2010.9
