Article reading comprehension answer retrieval system and device based on machine learning

A reading comprehension and machine learning technology, applied in the computer field, can solve the problem of high cost of labeling corpus, and achieve the effect of eliminating manual labeling, moderate accuracy and cost saving

Active Publication Date: 2020-06-05
文灵科技(北京)有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The embodiment of this specification provides an article reading comprehension answer retrieval system and device based on machine learning, which solves the technical problem of high accuracy of the answer retrieval system in the prior art but high cost of labeling corpus, and achieves the elimination of manual labeling Through the process of setting rules to generate machine annotations, the technical effect of moderate accuracy and no need for manual annotations is achieved, which saves costs

Method used

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  • Article reading comprehension answer retrieval system and device based on machine learning
  • Article reading comprehension answer retrieval system and device based on machine learning
  • Article reading comprehension answer retrieval system and device based on machine learning

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Embodiment 1

[0046] figure 1 It is a schematic flowchart of an article reading comprehension answer retrieval system based on machine learning in an embodiment of the present invention. Such as figure 1 shown. The system is applied to an article reading comprehension answer retrieval device based on machine learning, and the machine learning-based article reading comprehension answer retrieval processing device includes an input device and a display device, and the input device has a text input module, text A processing module, a memory, and a signal input module, the input device can be connected to a device that generates an output signal such as a keyboard, and the display device is connected to the input device to display the text processed by the input device such as the keyboard devices such as display screens. The system includes steps S101-S105.

[0047] S101: Extract the keywords of the first sentence, the second sentence and the question sentence in the article according to t...

Embodiment 2

[0060] Based on the same inventive concept as the machine learning-based article reading comprehension answer retrieval system in the foregoing embodiments, the present invention also provides a machine learning-based article reading comprehension answer retrieval device, such as figure 2 shown, including:

[0061] The first obtaining unit 11 is used to extract the keywords of the first sentence, the second sentence and the question sentence in the article according to the semantic rules, and obtain the first core word, the second core word and the question core word, wherein the first core The word is different from the second core word;

[0062] The second obtaining unit 12 is used to vectorize and represent the first core word, the second core word and the question core word according to the pre-training sentence model, and obtain the first core word vector, the second core word word vector and the core word vector of the question;

[0063] The third obtaining unit 13 is...

Embodiment 3

[0084] Based on the same inventive concept as the article reading comprehension answer retrieval system based on machine learning in the first embodiment, the present invention also provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, Steps for implementing any system of a machine learning-based article reading comprehension answer retrieval system described above.

[0085] Among them, in image 3 In, bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 will include one or more processors represented by processor 302 and various types of memory represented by memory 304 circuits linked together. The bus 300 may also link together various other circuits, such as peripherals, voltage regulators, and power management circuits, etc., which are well known in the art and thus will not be further described herein. The bus interface 306 pro...

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Abstract

The invention provides an article reading comprehension answer retrieval system and device based on machine learning. The method comprises the steps: extracting keywords of different sentences and question sentences in an article according to a semantic rule, and obtaining core words corresponding to the different sentences and question core words; vectorizing the core words of the sentences and the question core words according to a pre-trained statement model and obtaining core word vectors of the sentences and a question core word vector; calculating the similarity between the question coreword vector and the core word vectors of different sentences according to the cosine distance, and obtaining the similarities of different sentences; judging the similarities of different sentences;and taking sentences with high similarities as training corpora and inputting the training corpora into a neural network combined by a recurrent neural network and a multi-layer perceptron for training to obtain an answer retrieval neural network model. The technical problem of manually annotating corpora in the prior art is solved, machine annotation is generated by adopting a fixed rule, and thetechnical effects of moderate accuracy, no need of manual annotation and cost saving are achieved.

Description

technical field [0001] The embodiment of this specification relates to the field of computer technology, and in particular to a machine learning-based article reading comprehension answer retrieval system and device. Background technique [0002] At present, there are mainly two technologies in the field of question answering in articles, namely, search engines and supervised learning based on deep learning. Among them, search engines are based on keyword retrieval, with high recall rate, but low precision rate, and more search results than all others. The answers to the required questions are irrelevant and need to be identified before use. Supervised learning based on deep learning can achieve a high accuracy after a large amount of corpus training, but the cost of annotating corpus is high. [0003] However, in the process of realizing the technical solution of the invention in the embodiment of the present application, the inventor of the present application found that ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F40/30G06F40/289G06F16/35G06F16/33G06N20/00
CPCG06F16/3331G06F16/355G06N20/00
Inventor 宋永生张柳涛王楠王逸飞
Owner 文灵科技(北京)有限公司
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