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Semantic recognition method, device and related equipment combined with knowledge map entity information

A semantic recognition and knowledge graph technology, applied in semantic analysis, semantic tool creation, natural language data processing, etc., can solve the problem of low accuracy of semantic recognition

Active Publication Date: 2022-04-26
华润数字科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The embodiment of the present invention provides a semantic recognition method, device and related equipment combined with knowledge map entity information, aiming to solve the problem of low semantic recognition accuracy in the prior art

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  • Semantic recognition method, device and related equipment combined with knowledge map entity information
  • Semantic recognition method, device and related equipment combined with knowledge map entity information
  • Semantic recognition method, device and related equipment combined with knowledge map entity information

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Embodiment Construction

[0036] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0037] It should be understood that when used in this specification and the appended claims, the terms "comprising" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude one or Presence or addition of multiple other features, integers, steps, operations, elements, components and / or collections thereof.

[0038] It should also be understood that the terminology used ...

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Abstract

The embodiment of the invention discloses a semantic recognition method, device and related equipment combined with knowledge map entity information. The method includes calculating the hidden state vector of each training entity in the training corpus, as well as the adjacent semantic vector, word embedding vector and position vector of each word, and combining the hidden state vector, adjacent semantic vector, word embedding vector and position vector Obtain the input vector of each word; predict the input vector through the encoder of the Transformer model, and obtain the predicted probability of the semantics of the input vector; according to the probability between the predicted probability and the real semantics of the input vector, the model parameters of the encoder are calculated Optimized to obtain a semantic recognition model; finally, carry out semantic recognition through the semantic recognition model. The method makes the entity features acquired by the semantic recognition model more comprehensive, thereby improving the accuracy of semantic recognition by the semantic recognition model.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of semantic recognition, and in particular, to a method, device and related equipment for semantic recognition combined with knowledge map entity information. Background technique [0002] Pre-trained language recognition models have achieved good results in many natural language processing fields such as text classification, intelligent question answering, machine reading, and text summarization in recent years. The pre-training model is trained based on massive text data. Statistically speaking, massive text data itself contains extremely rich features. Therefore, combined with a neural network model with a strong fitting ability, it is possible to learn a wide range of semantic associations contained in the language. . [0003] At present, integrating knowledge graphs into pre-trained language recognition models has become an important means to further improve the effect of semantic...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F40/295G06F40/30G06F16/35G06F16/36
CPCG06F40/295G06F40/30G06F16/35G06F16/367
Inventor 王伟黄勇其于翠翠张黔
Owner 华润数字科技有限公司
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