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Zero sample relation extraction method and system based on dual contrast learning

A relationship extraction and sample technology, applied in the field of information detection, can solve problems such as difficulty in implementation

Active Publication Date: 2022-05-27
PEKING UNIV
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  • Claims
  • Application Information

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Problems solved by technology

This technology is in urgent need, and its downstream application scenarios are also extremely extensive, such as dynamic expansion of knowledge graphs, question answering systems, retrieval systems, etc., but its implementation is difficult

Method used

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  • Zero sample relation extraction method and system based on dual contrast learning
  • Zero sample relation extraction method and system based on dual contrast learning

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Embodiment Construction

[0032] The present invention will now be discussed with reference to exemplary embodiments. It should be understood that the discussed embodiments are only provided to enable those of ordinary skill in the art to better understand and thus implement the content of the present invention, and are not intended to imply any limitation on the scope of the present invention.

[0033] As used herein, the term "including" and variations thereof are to be read as open-ended terms meaning "including, but not limited to." The term "based on" is to be read as "based at least in part on". The terms "one embodiment" and "one embodiment" are to be read as "at least one embodiment."

[0034] In order to solve the technical problems mentioned in the above background art and better perform zero-sample relationship extraction, the present invention conducts an in-depth analysis on the problem of zero-sample relationship extraction, and finds that zero-sample relationship extraction can be solve...

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Abstract

The invention relates to the technical field of software detection, and provides a zero sample relation extraction method and system based on dual contrast learning, and the method comprises the steps: obtaining a sample data set, and dividing the sample data set into a training set, a verification set and a test set; preprocessing the training set; encoding the preprocessed samples, obtaining vector representation of each sample in combination with position encoding, and encoding labels of the samples in the training set to obtain vector representation of each label; calculating model loss by combining the comparative learning of the sample layer and the comparative learning of the label layer, and constructing a relation extraction model after calculating the model loss; inputting the verification set into the relation extraction model to obtain an optimal relation extraction model; and inputting the test set into the optimized relation extraction model to obtain a semantic matching result as a zero sample relation extraction result. According to the scheme of the invention, high efficiency and accuracy of zero sample relation extraction are ensured, and the problem of urgent demand for zero sample relation extraction in the prior art is solved.

Description

technical field [0001] The present invention relates to the technical field of information detection, and in particular, to a zero-sample relation extraction method, system, electronic device and computer-readable storage medium based on dual contrast learning. Background technique [0002] With the development of the Internet and the explosive growth of information on the Internet, people not only receive a large amount of new knowledge and news every day, but also a large number of new entities and relationship types appear on the Internet every day. The relationship extraction technology is a technology that judges the relationship between two entities by given context information and target entities (including head entity and tail entity). In previous studies, researchers have mainly focused on relation extraction with labels (i.e., relation names of head and tail entities, for example, the relation between Beijing and China is the capital, and the capital is the relatio...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06F40/30G06N3/04G06N3/08
CPCG06N3/08G06F40/30G06N3/045G06F18/22G06F18/214
Inventor 张世琨叶蔚李博谢睿
Owner PEKING UNIV
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