Intelligent search system and method for medical services

Abstract

The invention discloses an intelligent search system and method for medical services. The method comprises the steps of obtaining query information input by a user; carrying out entity extraction on the query information to obtain target entity words; searching the target entity words in a relational database; if the target entity words are not found, carrying out word segmentation retrieval on the target entity word in an ES database; taking the medical sub-libraries where the retrieved target entity words are located as target medical sub-libraries; if the target entity words are found, setting a table where the target entity words are located as a target medical table; in the ES database, carrying out non-word-segmentation retrieval on the target entity word in other medical sub-libraries except the medical sub-library corresponding to the target medical table; taking the medical sub-libraries of the retrieved target entity words and the medical sub-libraries corresponding to the target medical table as target medical sub-libraries; and obtaining and displaying the medical information indexed by the target entity word in the target medical sub-library. According to the invention, a user can be helped to accurately locate related diagnosis and treatment resources, and the medical experience and medical efficiency are improved.

Description

technical field [0001] The invention relates to the field of information search, in particular to an intelligent search system and method for medical services. Background technique [0002] At present, when searching for medical resources, various reservation registration platforms mostly adopt the traditional index-based retrieval method, and search based on keyword matching in relational databases, which often has the phenomenon of incomplete search, inaccurate search, and low search quality, especially Especially in the era of network information, it is difficult to use keyword matching to meet people's retrieval requirements, especially for large text retrieval, index retrieval is not only slow but also unable to segment the patient's input. [0003] The full-text retrieval technology based on Lucene and ElasticSearch (hereinafter referred to as ES) can segment words according to the meaning of words based on content, and then create indexes respectively, so as to achiev...

AI Technical Summary

Problems solved by technology

[0002] At present, when searching for medical resources, various reservation registration platforms mostly adopt the traditional index-based retrieval method, and search based on keyword matching in relational databases, which often has the phenomenon of incomplete search, inaccurate search, and low search quality, especially Especially in the era of network information, it is difficult to use keyword matching to meet people's retrieval requirements, especially for large text retrieval, index retrieval is not only slow but also unable to segment the patient's input

[0003] The full-text retrieval technology based on Lucene and ElasticSearch (hereinafter referred to as ES) can segment words according to the meaning of words based on content, and then create indexes respectively, so as to achieve the effect of natural language retrieval. However, due to the large number of professional terms in the medical industry, traditional word segmentation will produce The problem of excessive word segmentation, that is, words that should not be separated are segmented and then retrieved, which will also cause inaccurate retrieval

Images