Machine reading model training method and device, question and answer method and device

A machine and model technology, applied in the direction of instruments, special data processing applications, electrical digital data processing, etc., can solve problems such as few, difficult to implement, and low controllability of generative answers

Active Publication Date: 2018-12-07
ZHONGAN INFORMATION TECH SERVICES CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method is difficult to implement and requires a huge amount of corpus for training. At presen

Method used

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  • Machine reading model training method and device, question and answer method and device
  • Machine reading model training method and device, question and answer method and device
  • Machine reading model training method and device, question and answer method and device

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Embodiment 1

[0091] refer to figure 1 Shown, the machine reading model training method that the embodiment of the present invention provides, this method comprises steps:

[0092] 101. Obtain a training sample. The training sample includes a sample question and its corresponding sample article, as well as the real initial position and the real end position of the corresponding answer in the sample article.

[0093] Specifically, the present invention does not limit the specific acquisition process.

[0094] 102. Extract the question feature vector of the sample question and the article feature vector of the sample article.

[0095] Wherein, the question feature vector of the sample question and the article feature vector of the sample article are extracted, and the process may include the following steps:

[0096] (1) Generate word vectors and word vectors for sample questions and sample articles.

[0097] Specifically, the features of the sample questions and the features of the sample...

Embodiment 2

[0135] Based on the machine reading model trained in Embodiment 1, the embodiment of the present invention also provides a question-and-answer method. After the machine-reading model is deployed as a service, the question-and-answer method can quickly call the online The reading comprehension model extracts answers and returns them to the user.

[0136] refer to figure 2 As shown, the embodiment of the present invention provides a question answering method, the method includes steps:

[0137] 201. According to the question input by the user, filter out articles corresponding to the question from the article knowledge base.

[0138] Specifically, the question entered by the user and all articles in the article knowledge base are represented by the bag-of-words model, and the articles corresponding to the question are screened out based on the question-article bag-of-words vector.

[0139] In the specific implementation process, the user can input questions in the form of voi...

Embodiment 3

[0145] As the realization of the machine reading model training method in the first embodiment, the embodiment of the present invention also provides a machine reading model training device, refer to image 3 As shown, the device includes:

[0146] The obtaining module 31 is used to obtain training samples, the training samples include sample questions and corresponding sample articles, and the real initial positions and real end positions of the corresponding answers in the sample articles;

[0147] The extraction module 32 is used to extract the question feature vector of the sample question and the article feature vector of the sample article;

[0148]The fusion module 33 is used to fuse and process the question feature vector and the article feature vector using the neural network structure to form a fusion result;

[0149] Prediction module 34, for the prediction of the initial position and the end position of answer for inputting fusion result in the classifier;

[015...

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Abstract

The invention discloses a machine reading model training method and device, a question and answer method and a device, and belongs to the field of natural language processing. The machine reading model training method comprises the following steps: acquiring a training sample, wherein the training sample comprises a sample question and a corresponding sample article, a real initial position and areal final position of the corresponding answer in the sample article; extracting a question feature vector of the sample question and an article feature vector of the sample article, and using a neural network structure to fuse and process the question feature vector and the article feature vector to form a fusion result; inputting the fusion result into a classifier to perform prediction of theinitial position and the final position of the answer; performing error calculation on the predicted initial position and final position, and the real initial position and the real final position of the answer; and optimizing the neural network structure according to the error calculation result. According to the machine reading model training method and device, the question and answer method anddevice in the embodiment of the invention, the corresponding answer can be directly extracted from the entire associated article through end-to-end deep learning.

Description

technical field [0001] The invention relates to the field of natural language processing, in particular to a machine reading model training method and device, and a question answering method and device. Background technique [0002] There are many ways to implement the technical architecture of the mainstream question answering system, such as: search engine based on pure keyword matching, method of extracting semantic similarity features based on natural language processing, and sequence-to-sequence (seq2seq) generation based on deep learning dialog method. [0003] However, there are many problems in the existing question answering systems, as follows: [0004] For the retrieval-based question answering system, its retrieval-based question-answering method cannot achieve true semantic matching to the questions entered by the user, and often the answer is not what is asked. Some of these special cases can be handled by manually adding rules, but this method has high maint...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 倪博溢张永煦周笑添
Owner ZHONGAN INFORMATION TECH SERVICES CO LTD
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