Machine reading comprehension answer obtaining method based on multi-round attention mechanism

Abstract

The invention discloses a machine reading comprehension answer obtaining method based on a multi-round attention mechanism. The method comprises steps of performing word segmentation processing and vectorization processing on the questions and the texts corresponding to the questions respectively to obtain feature vectors, selecting a bidirectional long-short time memory network to encode contextsemantic information of the feature vectors, and performing modeling between the questions and the texts by using an attention mechanism to effectively capture information interaction between the questions and the texts. Attention of an article about a question is calculated through multiple rounds, context semantic information is fused, then BLSTM is used for coding the context semantic information, the above processes are repeated for multiple times, so that an nth text semantic vector is obtained, and a Self-Attention mechanism is used for obtaining a vector representation of the question;by calculating the similarity between the semantic vectors of the questions and the similarity of the semantic vectors, namely one representation of each word in the article in the question space, theaccuracy of predicting answers can be effectively improved, BLSTM and Attention are effectively combined, and the matching accuracy of the questions and the answers returned by text extraction can beimproved.

Description

technical field [0001] The invention belongs to the technical field of electronic information, and in particular relates to a method for obtaining answers for machine reading comprehension based on a multi-round attention mechanism. Background technique [0002] With the continuous development of technology and the Internet and the advent of the era of artificial intelligence, the total amount of digital information is growing exponentially. How to understand users' intentions and answer them is an urgent problem for major Internet companies and research institutions. However, how to accurately and quickly find the information resources you want from the messy and massive digital information, the simplest and most direct way is to use search engines such as Baidu to get the answers you want. With the development of search engines And progress, which brings great convenience to people's life. In recent years, the research on machine reading comprehension tasks has attracted ...

AI Technical Summary

Problems solved by technology

[0007] Some early machine reading comprehension models mostly use a one-way attention mechanism, which cannot obtain the connection between documents and questions very well.

During the coding process of documents and questions, it is inevitable that valid information will be lost

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