Text classification and display method, device, computer equipment and storage medium

Abstract

The invention relates to a text classification and display method and device, a computer device and a storage medium. The text classification method includes the steps of determining partial word classification results of target types from word classification results of text to be classified; adding classification marks of the target types on the text with the word classification results includingthe target types, and adding classification marks of non-target types on the text with the word classification results not including the target types; according to the text to be classified and the added classification marks, conducting model training to obtain a classification model; inputting each word classification result into the classification model and outputting the probability of each word classification result that the word classification result belongs to the target types; redefining each word classification result with the probability of belonging to the target types higher than or equal to a first probability threshold value as the word classification result of the target types, feeding back the added classification marks of the target types on the text with the word classification results including the target types, continuing processing until an iteration end condition is satisfied, and obtaining classification marks of the text to be classified. The scheme improves theprocessing efficiency.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a text classification and display method, device, computer equipment and storage medium. Background technique [0002] With the rapid development of science and technology, the era of big data is gradually coming, and the data processing methods are various. Among them, data classification has attracted more and more attention because it can play an important role in many aspects. [0003] In some scenarios, traditional methods need to manually add classification labels to a large amount of data. For example, when performing supervised machine learning training, it is necessary to prepare a large number of unclassified sample data in advance, and manually add classification marks to the full amount of large number of unclassified sample data one by one, so as to be based on the manually added classification marked sample data. Conduct supervised machine learning train...

AI Technical Summary

Problems solved by technology

[0004] Based on this, it is necessary to provide a text classification and display method, device, computer equipment and storage medium for the problem that the efficiency of adding classification marks to a large number of sample data manually by traditional methods is relatively low.

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