An Algorithm of Web Text Clustering Analysis Based on Fuzzy Set

Author

Peng, Yun ; Ding, Shu-liang

Author_Institution

Coll. of Comput. Inf. & Eng., Jiangxi Normal Univ., Nanchang, China

Volume

1

fYear

2008

fDate

20-22 Dec. 2008

Firstpage

109

Lastpage

113

Abstract

There are a large quantity of non-certain and non-structure contents in the Web text at the present time. It is difficult to cluster the text by some normal classification methods. An algorithm of Web text clustering analysis based on fuzzy set is proposed in this paper, and the algorithm has been described in detail by example. The technique can improve the algorithm complexity of time and space, increase the robustness of the algorithm. To check the accuracy and efficiency of the algorithm, the comparative analysis of the sample and test data is provided in the end.

Keywords

Internet; computational complexity; data mining; fuzzy set theory; pattern classification; pattern clustering; text analysis; Web text clustering analysis; algorithm complexity; fuzzy set; text classification; text mining; Algorithm design and analysis; Clustering algorithms; Computer science; Data mining; Dictionaries; Educational institutions; Frequency; Fuzzy sets; Information analysis; Text mining; clustering analysis; fuzzy set; membership function; web text;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Computational Technology, 2008. ISCSCT '08. International Symposium on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-3746-7

Type

conf

DOI

10.1109/ISCSCT.2008.139

Filename

4731386