Network text data detection method based on fuzzy cluster

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.

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...

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Problems solved by technology

[0004] In order to overcome the deficiencies of the prior art, such as insufficient depth of mining, slow execution speed, and low clustering accuracy, the present invention provides a network text data detection method based on fuzzy clustering, which can effectively improve the text classification in network security audits. Accuracy and reliability of the network content, thereby improving the acquisition efficiency of the target text in the network content, and realizing the intelligent retrieval of the network content

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