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Semantic representation model processing method, device, electronic device and storage medium

A semantic representation and model technology, applied in the computer field, can solve problems such as limited capacity of semantic representation models, difficulty in learning semantic representation models, and poor accuracy of semantic representation, so as to enrich semantic representation capabilities, improve text input efficiency, and improve accuracy Effect

Active Publication Date: 2020-06-30
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, current technologies such as BERT and XLNet have a single task goal during training, which makes it difficult for the semantic representation model trained by the existing technology to fully learn the various levels of information in the training corpus, which limits the ability of the existing semantic representation model. Semantic representation is less accurate

Method used

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  • Semantic representation model processing method, device, electronic device and storage medium
  • Semantic representation model processing method, device, electronic device and storage medium
  • Semantic representation model processing method, device, electronic device and storage medium

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Embodiment Construction

[0066] The following describes exemplary embodiments of the present application with reference to the accompanying drawings, which include various details of the embodiments of the present application to facilitate understanding, and should be regarded as merely exemplary. Therefore, those of ordinary skill in the art should realize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. Likewise, for clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0067] figure 1 This is a schematic diagram of the first embodiment of this application. Such as figure 1 As shown, the flowchart of the embodiment of the processing method of the semantic representation model of the present application is introduced in detail. Such as figure 1 As shown, the processing method of the semantic representation model of this embodime...

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Abstract

The application discloses a processing method, device, electronic equipment and storage medium of a semantic representation model, and relates to the technical field of artificial intelligence. The specific implementation scheme is: collect a training corpus including several training corpora; use the training corpus to train the semantic representation model based on at least two of word fragments, sentences and articles. In this application, by constructing unsupervised or weakly supervised pre-training tasks at three different levels of word fragments, sentences, and articles, the semantic representation model can learn knowledge of different levels of word fragments, sentences, and articles from massive data, enhancing the The ability of general semantic representation improves the processing effect of NLP tasks.

Description

Technical field [0001] This application relates to the field of computer technology, in particular to artificial intelligence technology, and specifically to a processing method, device, electronic device and storage medium of a semantic representation model. Background technique [0002] Artificial Intelligence (AI) is a new technological science that studies and develops theories, methods, technologies and application systems used to simulate, extend and expand human intelligence. Artificial intelligence is a branch of computer science. It attempts to understand the essence of intelligence and produce a new intelligent machine that can respond in a similar way to human intelligence. Research in this field includes robotics, language recognition, image recognition, Natural language processing (Natural Language Processing; NLP) and expert systems, etc. Especially in the field of NLP, it has become a hot topic for AI research in recent years. [0003] In the field of NLP, a neural...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F40/30
CPCG06F40/30G06F40/268G06F40/253G06F40/279G06N20/00G06F40/40
Inventor 孙宇王海峰王硕寰李宇琨冯仕堃田浩吴华
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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