Title :
Research on Text Clustering Algorithm Based on Improved K_means
Author_Institution :
Electron. Bus. Dept., Jiangxi Univ. of Finance & Econ., Nanchang, China
Abstract :
Text clustering is one of the difficult and hot research fields in the Internet search engine research. Using and improving K-means clustering techniques, a new text clustering algorithm is presented. Firstly, texts are preprocessed to satisfy succeed process. Secondly, the paper improves the gravity centers calculation method and algorithm flow of K-means cluster algorithm to improve efficiency and stability of original K_means algorithm. The experimental results indicate that the improved algorithm has a higher accuracy compared with the original algorithm, and has a better stability.
Keywords :
Internet; pattern clustering; search engines; text analysis; Internet search engine research; K-means clustering techniques; gravity centers calculation; text clustering algorithm; Business communication; Clustering algorithms; Finance; Gravity; Information retrieval; Internet; Iterative algorithms; Partitioning algorithms; Search engines; Stability; K-means; Text clustering; algorithm flow; gravity centers calculation;
Conference_Titel :
Future Computer and Communication, 2009. FCC '09. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3676-7
DOI :
10.1109/FCC.2009.65