Entity linking method and device based on semantic components

Abstract

The invention provides an entity linking method and device based on semantic components, and relates to the technical field of computers. The method comprises the steps of obtaining a to-be-linked entity from a medical data set; determining a standard entity candidate set of the to-be-linked entities in a medical knowledge graph, wherein the standard entity candidate set comprises a plurality of standard entities most similar to the to-be-linked entities; determining a semantic similarity score of each standard entity in the candidate set and a to-be-linked entity through a pre-trained semantic enhancement model; and linking the entity to be linked to the standard entity with the highest semantic similarity score in the candidate set. Therefore, the semantic component information can be added into the entity linking process, so that the semantic enhancement model can learn more information, and the entity linking accuracy is higher.

Description

Technical field [0001] The present invention relates to the field of computer technology, in particular to a method and device for entity linking based on semantic components. Background technique [0002] In the processing of big data of clinical medical records, due to differences in regions, hospitals, doctors, standards, etc., the same entity often has a large number of different expressions. Only by accurately identifying the same entity and targeting the limited physical space can the data be effectively processed. Perform statistics and calculations. Therefore, the medical term entity link is an essential part of the data processing process. [0003] The existing entity linking method generally reduces the number of candidates through algorithms such as classification, and then calculates the closest candidate through similarity calculation. As the core algorithm of the existing entity link system, similarity calculation is generally by modeling the features of things, tra...

AI Technical Summary

Problems solved by technology

[0004] In the existing entity linking methods, a large amount of labeled corpus is generally required, and it is difficult to add professional medical knowledge to features for calculation

In addition, the entity linking method based on similarity calculation can handle the situation where the candidates are quite different, but it is usually difficult to deal with the situation where the candidates are similar.

Especially the algorithm based on neural network cannot make good use of medical related knowledge, and the calculation process of the algorithm cannot be explained

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