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Improved natural language characteristic precise extracting method based on deep learning

A natural language and deep learning technology, applied in natural language data processing, special data processing applications, instruments, etc., can solve problems such as large error in feature extraction, low precision, and error in feature extraction

Active Publication Date: 2016-11-09
福州果集信息科技有限公司
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AI Technical Summary

Problems solved by technology

This method can quickly extract natural language features, but there are problems of large feature extraction errors and low precision.
Literature [12] proposes a natural language feature extraction method based on knowledge graphs. This method uses the statistical results presented by knowledge graphs to find the similarity between natural languages ​​and extract resource language features. Although this method can realize natural language features Extraction, but the extracted features are susceptible to errors caused by subjectivity, resulting in low extraction accuracy

Method used

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  • Improved natural language characteristic precise extracting method based on deep learning
  • Improved natural language characteristic precise extracting method based on deep learning
  • Improved natural language characteristic precise extracting method based on deep learning

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Embodiment Construction

[0085] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.

[0086] Such as figure 1 As shown, an improved method for accurately extracting natural language features based on deep learning of the present invention is characterized in that: comprising the following steps,

[0087] S1: Use the maximum entropy method to establish a conditional maximum entropy model for natural language. The specific implementation is as follows:

[0088] Assume that the natural language training sample attribute set is (x 1 ,y 1 ),(x 2 ,y 2 ),...,(x N ,y N ), then its probability distribution is as follows:

[0089] P ~ ( x , y ) = C ( x , y ) N ...

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Abstract

The invention relates to an improved natural language characteristic precise extracting method based on deep learning. The method includes the steps of establishing a natural language condition maximum entropy model by means of a maximum entropy method when basically analyzing natural language, selecting natural language property characteristics by means of an IFS algorithm on the basis of the model, selecting characteristics meeting reality by matching the natural language property characteristics, and precisely extracting the natural language characteristics by means of a deep learning method. When natural language characteristics are extracted by means of the improved extracting method, compared with a traditional extracting method, the improved extracting method has the advantages that the extracting accuracy is improved, the error rate is decreased, and certain practicability is achieved.

Description

technical field [0001] The invention relates to an improved method for accurately extracting natural language features based on deep learning. Background technique [0002] A natural language usually refers to a language that naturally evolves with culture, a language created for some specific purpose. with certain knowledge and uncertainty [1，2] . With the continuous development of computer technology, using natural language to communicate with computers has been the goal that people have been pursuing for a long time. [3,4] . Because you can use the computer in the language you are most used to, you dont need to spend a lot of time and energy learning various computer languages. [5,6] . People can also use it to further understand human language ability and intelligence mechanism. Research on natural language is the basis for effective communication between humans and computers, and is an important direction in the field of computer science and artificial intelligence...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/20G06F40/00
CPCG06F40/00
Inventor 张福泉
Owner 福州果集信息科技有限公司
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