Application method and device of semantic comprehension recall model, equipment and storage medium

Abstract

The invention discloses an application method and device of a semantic comprehension recall model, equipment and a storage medium. The application method comprises the following steps: extracting M pieces of corpus information having a first relationship with input information from a semantic sample library corresponding to a target semantic comprehension recall model; executing pre-training on the M pieces of corpus information and the input information, and converting the M pieces of corpus information and the input information into X word vectors; inputting each word vector in the X word vectors into a first presentation layer, and executing semantic recognition to obtain X pieces of first semantic information; inputting each word vector into a second presentation layer, executing semantic recognition, and obtaining X pieces of second semantic information; and determining M matching thresholds between the M pieces of corpus information and the input information by utilizing a preset algorithm according to the X pieces of first semantic information and the X pieces of second semantic information. In this way, the accuracy of determining the correlation between the corpus information and the input information is improved, and the accuracy of follow-up content search by a user is further improved.

Description

technical field [0001] The present invention relates to the field of artificial intelligence and digital medicine, in particular to an application method, device, device and storage medium of a semantic understanding recall model. Background technique [0002] At present, with the continuous development of information technology, it is more and more convenient to find and search for information through the network, and the efficiency of finding and searching for information is constantly improving. [0003] In the related art, for different industries, different recall models can be set in advance, and when a user searches, the recall model can match the user with appropriate content according to the specific search content. Among them, the recall model is a learning and training model, specifically, a model trained through massive samples. For example, for a recall model that is used to search for doctors, the recall model can be trained by setting a large amount of doctor...

AI Technical Summary

Problems solved by technology

[0004] However, due to the simple and single sample training process of the existing recall model, it is easy to have a high matching error rate when using the recall model to perform search tasks and obtain matching semantic content.

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