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This paper first studies the methods of web documents mining and text clustering, and summaries the fuzzy clustering algorithms and similarity measure functions, then proposes a modified similarity function which can solve the problems of feature selection and feature extraction in high-dimensional space. Finally, this paper puts forward to a dynamic fluzzy clustering algorithm(DCFCM) by combining...
Rapid progress of network arouses much attention on Internet public opinion, it is important to grasp the internet public opinion in time and understand the trends of their opinion correctly. Text mining plays a fundamental role in categorization and monitoring of internet public opinion, but internet public opinion is much more difficult than pure-text process because of their semi-structured characteristic...
Text clustering is a hot and essential topic in data mining and information retrieval. This paper proposed a KP-FCM clustering method, which used the key phrases as text features and applied the Fuzzy c-means (FCM) as clustering algorithm. In this method, key phrases were extracted by an algorithm based on suffix array. Experimental results on two standard text clustering benchmark corpuses, OHSUMED...
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