Medical field entity classification method fusing entity keyword features

A classification method and keyword technology, applied in the field of text processing, can solve problems such as wrong extraction results, accuracy affecting accuracy, and inability to directly integrate word-level features, so as to achieve the effect of improving accuracy

Pending Publication Date: 2021-03-16
BEIJING INFORMATION SCI & TECH UNIV
View PDF1 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Word-level data is often obtained through various word segmentation tools. Wrong word segmentation results may lead to wrong extraction results. The accuracy of word segmentation will directly affect the accuracy of entity extraction.
Most of the features that can assist in entity extraction, such as part of speech, w

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Medical field entity classification method fusing entity keyword features
  • Medical field entity classification method fusing entity keyword features
  • Medical field entity classification method fusing entity keyword features

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0033] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, not to limit the present application. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

[0034] Those skilled in the art can understand that, unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meanings as commonly understood by those of ordinary skill in the art to which this application belongs. It should also be understood that terms, such as those defined in commonly used dictionaries, should be understood to have m...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a medical field entity classification method fusing entity keyword features. The method comprises the steps: text vectorization operation; feature extraction; and sequence annotation. According to the medical field entity classification method fusing entity keyword features provided by the embodiment of the invention, a TFIDF is adopted to assist in constructing a keyword table, the keywords are used as feature input models, a BERT model is adopted to perform text vectorization operation to generate word vectors, the word vectors are input into a BILSTM-CNN hybrid modelto learn features, and then sequence labeling is performed through a CRF layer, so that medical field entity classification can be realized, and the accuracy, recall rate and F1 value of medical field entity classification can be greatly improved.

Description

technical field [0001] The present application relates to the technical field of text processing, in particular to a method for classifying entities in the medical field by integrating entity keyword features. Background technique [0002] The advent of the big data era has brought convenience to obtaining information. In the face of a large amount of information, information extraction can help people quickly obtain and analyze effective information from a large number of documents, so information extraction has been widely used. Entity extraction is a very important content in information extraction, and it is also a basic task for building knowledge graphs, dialogue systems, machine translation, etc. In recent years, methods such as machine learning and deep learning have also been widely used in entity extraction research. The emergence of smart medical care has broken the confinement of traditional medical care. Under the background of Internet + medical health, the app...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F40/295G16H15/00G06N3/04
CPCG06F40/295G16H15/00G06N3/044G06N3/045
Inventor 吕学强游新冬董志安
Owner BEIJING INFORMATION SCI & TECH UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap