Document classifying method based on network measure index

Abstract

The invention relates to a document classifying method based on a network measure index. The document classifying method comprises a sample training phase and a document classifying phase. The sample training phase comprises the first step of sample collecting, the second step of text segmenting, the third step of word class analyzing, the fourth step of function word and name removing, the fifth step of word frequency counting, the sixth step of characteristic set Vd establishing, the seventh step of characteristic network peak establishing, the eighth step of characteristic network edge establishing, the ninth step of average degree calculating, the tenth step of cluster coefficient calculating, the eleventh step of characteristic path length calculating and the twelfth step of network measure index interval obtaining. The document classifying phase comprises the first step of processing a document to be classified and the second step of judging document classification. According to the document classifying method, classifying is accurate, classifying efficiency is high, the problem that according to an existing classifying method, scientific and technical literature, novels and prose cannot be distinguished is solved, and a scientific classification method and a theoretical foundation is laid for automatic distinguishing of the scientific and technical literature, the novels and the prose.

Description

technical field [0001] The present invention relates to a document classification method based on network metrics, and more specifically, to a method based on network metrics that distinguishes document types based on the different metrics of the characteristic network determined by the characteristics of words used in different documents. Document classification method. Background technique [0002] With the development and progress of Internet technology, the document resources in the network are constantly enriched, including literary works such as novels and essays that enrich people's spiritual life, and scientific and technological documents that provide people with knowledge and lay the foundation for scientific research. The crystallization of technology and technology is the precious wealth of human civilization. However, with the advent of the era of big data, the exponential growth of massive resources poses challenges for the effective organization and managemen...

AI Technical Summary

Problems solved by technology

However, without the dependence of the topic, these classification algorithms cannot macroscopically establish an effective classification model for documents without topic restrictions before the domain is determined.

The above problems exist in the distinction between literary works and scientific and technological documents, that is, it is impossible to effectively classify whether a document belongs to a scientific and technological document, a novel or an essay

Because the fields and themes involved in literary works and scientific literature are infinite, and when the fields and themes involved in different types of documents are still intersecting, it is impossible to provide accurate category definitions during the training phase, and it is also impossible to extract features that can represent categories. value set, so it is difficult to build a classification model for this classification problem

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