Bi-LSTM label recommendation method based on attention mechanism

Abstract

The invention discloses a Bi-LSTM label recommendation method based on an attention mechanism. The Bi-LSTM label recommendation method based on the attention mechanism comprises the following steps: collecting an experimental data set; analyzing specific text data from the experimental data set; preprocessing the text data; extracting semantic features from the preprocessed question text description; constructing a multi-label classification model; recommending a proper label for the new problem through the constructed multi-label classification model; and evaluating and analyzing a label recommendation result. The method has the beneficial effects that the label recommendation task is mainly converted into the multi-label classification problem through the Bi-LSTM model based on the attention mechanism, the labels are automatically recommended according to the text description content of the problem, and the label recommendation accuracy is improved.

Description

technical field [0001] The present invention relates to the technical field of tag recommendation, in particular to a Bi-LSTM tag recommendation method based on attention mechanism. Background technique [0002] Today, the rapid development of human science and technology has not only significantly improved people's living standards, but also brought great convenience to people's daily life. The ever-changing Internet technology is an important part of science and technology since the 21st century. It has gradually become a necessity of people's life from scratch. Compared with traditional ways of obtaining information such as telephones, radios, televisions, and broadcasts, the transmission of information through the Internet has the advantages of large amount of information transmission, diversified information, and fast information transmission speed. It is precisely because of the diversity, convenience and timeliness of information delivered by Internet technology that...

AI Technical Summary

Problems solved by technology

And because there are differences in expression habits among different users, for the same problem, they may give labels with similar meanings but different descriptions, for example, C# is often expressed as Cshape, and .NET is expressed as DotNET. Both problems lead to a significant expansion of the set of tags that a software information site needs to maintain

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