Method and system for performing machine learning process for text classification

Abstract

A method and a system for performing a machine learning process for text classification are provided. The method comprises the steps of: obtaining a labeled text set; providing a user with an option corresponding to a default model algorithm, and with an option corresponding to at least one candidate model algorithm; training a classification model using the labeled text set according to a specific candidate model algorithm, when the user selects a specific candidate model algorithm among the at least one candidate model algorithm by the option corresponding to at least one candidate model algorithm; analyzing the labeled text in the labeled text set, obtaining information about at least one of an labeled text length, the number of labeled texts and the number of labeled types when the user selects the default model algorithm by the option corresponding to the default model algorithm; and determining a model algorithm for the text classification based on the information; and training the classification model using the labeled text set according to the determined model algorithm.

Description

technical field [0001] The following description relates to the field of text classification, and more specifically, to a method and system for performing a machine learning process for text classification. Background technique [0002] In the real world, text data is very rich, and users need to use different technical means to process text data in various scenarios. Text classification refers to the automatic labeling of each text in a text set according to a certain classification system or standard. Traditional manual or rule-based solutions cannot handle large-scale data volumes and text classification in complex scenarios, while machine learning (including deep learning, etc.) is very suitable for solving large-scale data classification problems. [0003] However, machine learning technology has a high technical threshold. Relevant personnel need to master very professional machine learning knowledge to be able to find model algorithms suitable for text classification...

AI Technical Summary

Problems solved by technology

However, this makes the selection of the classification model algorithm have a great relationship with the scene of the text data set (for example, the content of the text, etc.), for example, the scene of comment sentiment classification, the scene of news topic classification, etc., if the text to be classified is new scene, it is still difficult to effectively select the model

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