The invention discloses a text classification method, device and equipment, relates to the technical field of text classification, and aims to enable a network platform to accurately classify texts formed by meal description information and improve the text classification effect. The method comprises the steps of acquiring text features formed after meal description information is processed; respectively inputting the text features into pre-trained text classification models with different network structures for prediction, wherein the text classification model is used for predicting a probability value of the text feature on each category, and the classification result is a category corresponding to the text feature when the predicted probability value is the highest; and determining thecategory with the highest proportion value as the final classification result of the text feature mapping by counting the proportion value of the categories in the plurality of classification resultsof the text feature mapping.

Text classification method, device and equipment

The invention discloses a text classification method and device. The method comprises the following steps: receiving a to-be-classified text; Inputting the to-be-classified text as input data into anintegrated classifier so as to classify the to-be-classified text through the integrated classifier; If classification fails, inputting the to-be-classified text into a search engine, so that the to-be-classified text is searched through the search engine, and acquiring a search result; Adjusting the input data based on the search result to obtain adjusted input data; And inputting the adjusted input data into the integrated classifier so as to classify the to-be-classified text through the integrated classifier. According to the method, the to-be-classified texts are secondarily classified incombination with the search engine, and the problems that in the prior art, some to-be-classified texts with complex semantics and uncommon semantics are low in recognition rate, wrong in classification or not accurate enough are solved.

text classification method and device

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text classification method and device