Industry classification method and system for text publishing

Abstract

The invention discloses an industry classification method and system for text publishing. The method comprises the following steps: conducting first level industry category feature word collection excavating and second level industry category module training, and establishing a two-level hierarchical category system composed of the first level industry category feature word collection and the second level industry category feature word collection; conducting first level industry and second level industry classification to the published text according to the two-level hierarchical category system. The method and system provided by the invention can improve the accuracy and recall rate of the industry category of the published text.

Description

Technical field [0001] The present invention relates to the field of Internet technology, in particular to an industry classification method and system for publishing text. Background technique [0002] At present, the industry classification of search retrieval strings (query), and search terms and published texts submitted by users in an information retrieval system is essentially a short text classification technology. Based on the application scenarios of the information retrieval system, it is usually necessary to manually label the classification system. Common text classification methods in the prior art include: Naive Bayes (Bayes), Neural Network (Nnet), Support Vector Machine (SVM, Support Vector Machine), k-Nearest Neighbor (kNN, k-Nearest Neighbor) statistical classification Algorithms and classification methods based on manual inference rules. [0003] Limited by the application scenarios of the information retrieval system, and the characteristics of the short and s...

AI Technical Summary

Problems solved by technology

[0005] In view of this, the main purpose of the present invention is to provide an industry classification method and system for publi...

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