Title :
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
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;
Conference_Titel :
Computer Science and Computational Technology, 2008. ISCSCT '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3746-7
DOI :
10.1109/ISCSCT.2008.139
