Network text data detection method based on fuzzy cluster

A network text and fuzzy clustering technology, which is applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as slow execution speed, insufficient mining depth, and low clustering accuracy
CN101763404AInactive Publication Date: 2010-06-30SHAANXI DEVTEK TECH DEV
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Patent Information

Authority / Receiving Office
CN ยท China
Patent Type
Applications(China)
Current Assignee / Owner
SHAANXI DEVTEK TECH DEV
Publication Date
2010-06-30
Estimated Expiration
Not applicable ยท inactive patent

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Abstract

The invention discloses a network text data detection method based on fuzzy cluster. The method comprises the following steps: firstly preconditioning the extracted network content; extracting features of preconditioned network content which is needed to cluster, clustering, setting initial clustering number, wherein during the clustering process, a clustering number is matched with a membership matrix, each membership matrix contains an average information entropy, the average information entropy selects initial clustering center according to density function, the clustering number is modified in algorithm iteration process, and when the average information entropy is the minimum value, the corresponding clustering number is an optimal clustering number; and finally returning the clustering result to the user. The invention has efficient intelligent clustering effect and can adjust the clustering precision while considering the clustering speed according to different applications.
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Description

technical field

[0001] The invention relates to a data detection method, in particular to a network text data detection method. Background technique

[0002] About 80% of the information in the network is in the form of text, so the research on text data mining technology has become an increasingly popular and very important research topic in data mining. Web content clustering is a fully automatic processing process for grouping similar texts in web content into a group, and it is an unsupervised learning process. The purpose of clustering is to distinguish and classify physical or abstract objects according to the similarity between objects. According to the form of data division, the clustering method can be divided into: when there is a clear boundary in the division, it is called hard division, that is, the data is divided into a certain class; the division without clear boundaries is called fuzzy division, that is, the given data is divided into The form of the degre...

Claims

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