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

A technology for reading comprehension and acquisition methods, which is applied in the field of machine reading comprehension answer acquisition based on multi-round attention mechanism, which can solve problems such as inability to obtain documents and question connections, loss of effective information, etc., and achieve multiple information Effects of Interaction, Accuracy Improvement and Precision Improvement

Active Publication Date: 2019-08-02
XI AN JIAOTONG UNIV
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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

Method used

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

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Embodiment Construction

[0051] The present invention is described in further detail below in conjunction with accompanying drawing:

[0052] A machine reading comprehension method based on a multi-round attention mechanism, comprising the following steps,

[0053] Step 1, obtaining the text corresponding to the question and the question;

[0054] Step 2, performing word segmentation and vectorization processing on the question, selecting the Embedding feature as the feature vector, and obtaining the question feature vector corresponding to each word in the question;

[0055] Step 3, performing word segmentation and vectorization processing on the text, selecting five features of Embedding, Exact_match, POS, NER and TF as feature vectors, and obtaining text feature vectors corresponding to each word in the text;

[0056] Step 4, use the question feature vectors corresponding to each word in the question as the input of the bidirectional long-term short-term memory network model, and obtain the semant...

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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 ...

Claims

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Application Information

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IPC IPC(8): G06F16/33G06F16/332G06F17/27
CPCG06F16/3329G06F16/3344G06F40/30
Inventor 刘均孙申魏笔凡武云封曾宏伟麻珂欣
Owner XI AN JIAOTONG UNIV
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