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Training method, device, equipment and medium of named entity recognition model

A named entity recognition and training method technology, applied in neural learning methods, biological neural network models, instruments, etc., can solve the problems of low recognition accuracy and slow training speed of named entity recognition models, so as to shorten the training time, improve the Forecast speed and forecast accuracy, the effect of reducing time

Active Publication Date: 2022-02-18
PING AN TECH (SHENZHEN) CO LTD
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The purpose of the present invention is to provide a named entity recognition model training method, device, equipment and medium to solve the technical problems of slow training speed and low recognition accuracy of named entity recognition models in the prior art

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  • Training method, device, equipment and medium of named entity recognition model
  • Training method, device, equipment and medium of named entity recognition model
  • Training method, device, equipment and medium of named entity recognition model

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Embodiment Construction

[0058] 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 only some, not all, embodiments of the present invention. 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.

[0059] The terms "first", "second", and "third" in the present invention are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of indicated technical features. Thus, features defined as "first", "second", and "third" may explicitly or implicitly include at least one of these features. In the description of the present invention, "plurality" means at least two, such a...

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Abstract

The present invention relates to the technical field of natural language processing, in particular to a training method, device, equipment and medium for a named entity recognition model. In the training method, device, equipment and medium of the named entity recognition model of the present invention, the named entity recognition model uses the precision parameter as the reward signal, and calculates the first reward of each candidate object in the word vector matrix through the change of the precision parameter, and then Calculating the second reward at each time step based on the first reward can better reflect the contribution of each candidate object to the prediction result, and can better evaluate the effectiveness of different embedding word vector matrices obtained after masking , it is beneficial for the named entity recognition model to be sampled closer to the embedded word vector matrix with better effectiveness, which improves the training speed of the named entity recognition model, and at the same time improves the prediction speed and prediction accuracy of the named entity recognition model after training .

Description

【Technical field】 [0001] The present invention relates to the technical field of natural language processing, in particular to a training method, device, equipment and medium for a named entity recognition model. 【Background technique】 [0002] With the development of artificial intelligence (AI) technology, natural language processing (Natural Language Processing, NLP) technology in speech recognition, speech translation, understanding complete sentences, understanding synonyms of matching words, and generating grammatically correct complete sentences and Paragraphs, etc. are widely used. As a basic task of natural language processing, the purpose of named entity recognition (Named Entities Recognition, NER) is to identify three categories (entity category, time category and number category) and seven subcategories (person name, organization name) in the text to be processed. , Place Name, Time, Date, Currency, and Percentage) named entities. [0003] In the prior art, wh...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F40/295G06F40/44G06F40/284G06N3/04G06N3/08
CPCG06F40/295G06F40/44G06F40/284G06N3/04G06N3/084
Inventor 于凤英王健宗
Owner PING AN TECH (SHENZHEN) CO LTD
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