Medical text-oriented entity relationship joint extraction method

An entity-relationship and text technology, applied in the field of entity-relationship joint extraction for medical texts, can solve the problems of insufficient interaction ability and error transmission between the entity extraction module and the relationship extraction module, so as to improve the efficiency of joint extraction, increase utilization rate, improve The effect of interactivity

Active Publication Date: 2020-07-03
SOUTHWEST JIAOTONG UNIV
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Problems solved by technology

[0007] (1) The error transmission problem caused by the pipeline entity and relation extraction method;
[0008] (2) The information sparse problem of multiple entities and multiple

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  • Medical text-oriented entity relationship joint extraction method
  • Medical text-oriented entity relationship joint extraction method
  • Medical text-oriented entity relationship joint extraction method

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Embodiment Construction

[0057] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0058] Such as figure 1 and figure 2 As shown, it is a flow chart and a network structure diagram of the method for joint entity-relationship extraction oriented to medical texts of the present invention. According to the triplet composed of entity relations, the present invention makes a two-stage joint extraction data set, utilizes the ability of bidirectional long-term short-term memory network to model long-distance dependence, and the ability of convolutional neural network to represent local context, and adopts attention mechanism to capture The correlation between contexts enables the mod...

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Abstract

The invention discloses a medical text-oriented entity relationship joint extraction method. The method comprises the following steps of: recombining a medical text entity relationship data set according to a triple mode; vectorization representation is carried out on the medical text statement; a parameter sharing layer is constructed by adopting a bidirectional long-short-term memory network anda self-attention mechanism; predicting a head entity label by adopting a softmax function, performing relation-tail entity joint decoding by adopting CNN-softmax, enhancing joint decoding representation by combining a head entity prediction result, and training a parameter sharing layer and a joint decoding layer by adopting a joint loss function optimization mode. According to the method, the problems that entities and relationship categories and positions in the medical text are distributed unevenly, and multiple pairs of relationships appear in the same sentence at the same time are solved, and the quality and efficiency of entity relationship extraction of the medical text can be improved.

Description

technical field [0001] The invention belongs to the technical field of medical text entity recognition, and in particular relates to a medical text-oriented entity-relationship joint extraction method. Background technique [0002] With the rapid development of natural language processing technology, especially the continuous application in vertical fields, it has greatly promoted the transition of my country's medical services from "informatization" to "intelligence". Extracting structured knowledge from free medical texts such as electronic medical records and biomedical literature is the basis for smart medical applications such as intelligent medical guidance, interrogation, and clinical decision-making assistance. It is also an important research content for building medical knowledge graphs. The joint extraction of entities and relationships is one of the core tasks of information extraction, which specifically refers to automatically identifying the location range and...

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Application Information

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IPC IPC(8): G06F40/279G06F16/35G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06F16/35G06N3/047G06N3/045G06F18/2411
Inventor 滕飞马敏博李双庆姚远曾嵛刘赟
Owner SOUTHWEST JIAOTONG UNIV
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