Label classification method, data processing equipment and readable storage medium

Abstract

The invention discloses a label classification method, data processing equipment and a readable storage medium, and the method comprises the steps: obtaining to-be-processed data, wherein the to-be-processed data comprises to-be-processed corpus; extracting semantic features of the to-be-processed data, and performing logical operation processing on the extracted semantic features and the to-be-processed data to obtain fusion features of the to-be-processed data; based on the fusion features of the to-be-processed data, calculating the numerical value of each candidate category label so as torepresent the association degree of each candidate category label and the to-be-processed corpus; and based on the numerical value of each candidate category label, obtaining the candidate category label of which the numerical value meets a preset first selection condition, and obtaining a category label prediction set. By adopting the scheme, the accuracy of a label classification prediction result can be improved.

Description

technical field [0001] The embodiments of this specification relate to the field of information processing technologies, and in particular, to a label classification method, data processing equipment, and a readable storage medium. Background technique [0002] In the era of the explosion of Internet information, in order to quickly obtain the required information from the massive information on the Internet, Internet information will be classified and tagged with the corresponding classification. It is represented by key features that are easy to identify, so that users can search and filter. [0003] At present, the labeling of Internet information usually adopts two methods: manual classification and automatic classification. Among them, manual methods are costly and inefficient, and cannot meet the growth rate of Internet information. The automatic classification method needs to use a large amount of training data to train the label classification model in the early st...

AI Technical Summary

Problems solved by technology

Among them, manual methods are costly and inefficient, and cannot meet the growth rate of Internet information

The automatic classification method needs to use a large amount of training data to train the label classification model in the early stage, and the existing label classification model structure has weak generalization ability and poor versatility, resulting in low accuracy of label classification prediction results

Images