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Biomedical text representation method for modeling global and local context interaction

A biomedical and text representation technology, applied in the field of biomedical text representation, can solve the problems of not being able to obtain text representation, affecting the effect of bioinformatics tasks, and avoiding time-consuming and labor-intensive effects.

Active Publication Date: 2020-09-25
HUAZHONG NORMAL UNIV
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Problems solved by technology

Therefore, direct application of existing text modeling methods cannot obtain ideal text representation, which will affect the effect of downstream bioinformatics tasks. Therefore, a biomedical text representation method for modeling global and local context interactions is designed to optimize above question

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  • Biomedical text representation method for modeling global and local context interaction
  • Biomedical text representation method for modeling global and local context interaction
  • Biomedical text representation method for modeling global and local context interaction

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Embodiment Construction

[0048] In order to make the technical solutions of the present invention clearer and clearer to those skilled in the art, the present invention will be further described in detail below in conjunction with the examples and accompanying drawings, but the embodiments of the present invention are not limited thereto.

[0049] like figure 1 As shown, a biomedical text representation method for modeling global and local context interaction provided in this embodiment includes the following steps:

[0050] Step 1: Suppose the given biomedical text is a sequence of L sentences (S 1 ,...,S i ,...,S L ), where each sentence S i Expressed as a sequence of words in the sentence;

[0051] Step 2: The vector representation of each word is concatenated by word embedding, position embedding and entity type embedding;

[0052] Step 3: Through the input module, each sentence S in the given text i can be expressed as a matrix X i , where the jth row in the matrix represents the vector re...

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Abstract

The invention discloses a biomedical text representation method for modeling global and local context interaction, and belongs to the field of biomedical text representation methods. According to themethod, a given biomedical text is a sequence (S1,..., Si,..., SL) consisting of L sentences, wherein each sentence Si is expressed as a sequence composed of the words in the sentence; each sentence Si in the given text can be expressed as a matrix Xi through an input module, and the initial expression, obtained by the input module, of the biomedical text is input into an expression learning module for further text modeling, wherein each word is used as a node, a syntax dependence tree obtained by an open source tool Stanford CoreNLP is used as a topological structure between the nodes, and modeling is performed on local context information in Si by applying two layers of GCNs; a hypergraph concept is introduced to aggregate the local context information to obtain a representation that a corresponding node in the hypergraph contains global context information; and finally information interaction of local and global contexts is modeled to learn rich representations of related concepts in each sentence.

Description

technical field [0001] The invention relates to a biomedical text representation method, in particular to a biomedical text representation method for modeling global and local context interaction, and belongs to the technical field of biomedical text representation methods. Background technique [0002] In recent years, the field of biomedicine has developed vigorously, and biomedical literature has shown an explosive growth trend. How to quickly and accurately obtain target information from a large amount of biomedical text data is a topic with application prospects and research significance. Effective modeling of biomedical text is the basis for effective information extraction. Existing text modeling methods can be roughly divided into three categories: (1) Traditional text modeling methods, using feature selection or feature extraction methods to obtain text features, and on this basis, apply classic classification or clustering algorithms for classification and cluster ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/50G06F40/284G06F40/253G06F40/205G06F16/901
CPCG16H50/50G06F40/284G06F40/253G06F40/205G06F16/9024
Inventor 赵卫中张晋咏
Owner HUAZHONG NORMAL UNIV
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