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Method and device for extracting main component in field of medical treatment

A technology of main components and extraction methods, applied in the medical field, can solve problems such as a large number of manually labeled data, complex processes, and difficulty in adapting to new fields.

Inactive Publication Date: 2017-12-15
深圳市空谷幽兰人工智能科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the prior art, relation extraction adopts a rule-based extraction method to extract relations by defining description rules defined by domain experts. This method requires a large amount of manual labeling data, and it is difficult to adapt to new fields. Afterwards, a relation extraction method based on machine learning appeared. The process of this method Complicated etc.

Method used

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  • Method and device for extracting main component in field of medical treatment
  • Method and device for extracting main component in field of medical treatment
  • Method and device for extracting main component in field of medical treatment

Examples

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no. 1 example

[0029] see figure 2 , an embodiment of the present invention provides a method for extracting main components in the medical field, and the method may include: step S200, step S210, and step S220.

[0030] Step S200: Obtain the corpus to be extracted.

[0031] Step S210: Match the to-be-extracted corpus with a plurality of pre-stored templates respectively, and acquire a successfully matched template and a matching result corresponding to the successfully matched template.

[0032]As an implementation, the pre-stored multiple templates are pre-stored multiple templates sorted by length, and based on step S210, further, the corpus to be extracted and the pre-stored multiple templates sorted by length are sequentially Matching is performed respectively, and a successfully matched template and a matching result corresponding to the successfully matched template are acquired. In this embodiment, the corpus to be extracted can be matched with multiple pre-stored templates throug...

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Abstract

The embodiment of the invention provides a method and device for extracting a main component in the field of medical treatment, and relates to the field of medical treatment. The method comprises the steps that a to-be-extracted corpus is acquired; the to-be-extracted corpus is matched with a plurality of pre-stored templates, and the successfully matched template and a matching result corresponding to the successfully matched template are acquired; whether the successfully matched template meets preset extraction conditions or not is judged, and if yes, the matching result corresponding to the successfully matched template meeting the preset extraction conditions is obtained to serve as the main component corresponding to the to-be-extracted corpus, so that the corpus is matched through the template, the main component of the corpus is extracted, and the method is simple, rapid and efficient.

Description

technical field [0001] The present invention relates to the medical field, in particular to a method and device for extracting main components in the medical field. Background technique [0002] In the medical field, the machine can automatically identify the medical-related main parts and corresponding states in the user's description (for example, "I had a stomachache yesterday", and the corresponding main parts and states (subject components) are "stomach pain"). This recognition process is called medical subject component extraction, which belongs to the category of relation extraction. In the prior art, relation extraction adopts a rule-based extraction method to extract relations by defining description rules defined by domain experts. This method requires a large amount of manual labeling data, and it is difficult to adapt to new fields; after that, a relation extraction method based on machine learning appeared. The process flow of this method Complicated etc. Con...

Claims

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Application Information

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IPC IPC(8): G06F17/27G06F17/30
CPCG06F16/3329G06F16/951G06F40/289
Inventor 熊子奇姚佳
Owner 深圳市空谷幽兰人工智能科技有限公司