Knowledge representation learning method, device, equipment and storage medium
A knowledge representation and learning method technology, applied in the field of devices, knowledge representation and learning methods, equipment, and storage media, can solve the problems of data sparseness, time-consuming and labor-intensive problems, and achieve the effect of solving data sparseness problems and improving performance
Active Publication Date: 2020-12-25
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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Problems solved by technology
Designing a knowledge map not only has the disadvantage of time-consuming and laborious, but also suffers from the problem of data sparsity
Method used
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[0019] Exemplary embodiments of the present application are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present application to facilitate understanding, and they should be regarded as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
[0020] It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and embodiments.
[0021] figure 1 It shows an exemplary system architecture 100 to which emb...
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The embodiment of the present application discloses a knowledge representation learning method, device, device, and storage medium, and relates to the technical fields of natural language processing, deep learning, and knowledge graph. A specific implementation of the method includes: sampling the knowledge graph subgraph from the knowledge base; serializing the knowledge graph subgraph to obtain serialized text; using the pre-trained language model to read the serialized text in the order on the knowledge graph subgraph Text, learn the knowledge representation of each word in the serialized text. The knowledge representation learning in this embodiment is oriented to the entity and relation representation learning in the knowledge base, which can efficiently calculate the semantic association of entities and relations in a low-dimensional space, effectively solve the problem of data sparsity, and improve the performance of knowledge acquisition, fusion and reasoning. obvious improvement. Using the powerful knowledge acquisition and context analysis capabilities of the pre-trained language model, the knowledge representation learned by the pre-trained language model can better represent the complex relationships in the knowledge base.
Description
technical field [0001] The embodiment of the present application relates to the field of computer technology, specifically to the technical fields of natural language processing, deep learning, and knowledge graph, and especially to a knowledge representation learning method, device, device, and storage medium. Background technique [0002] A knowledge base may refer to a database that stores related data in an orderly manner. Generally, a knowledge base can be represented as a network, with nodes representing entities and edges representing relationships between entities. In the form of network representation, it is usually necessary to design a special knowledge graph to calculate and store and utilize the knowledge base. Designing knowledge graphs is not only time-consuming and labor-intensive, but also plagued by data sparsity. Therefore, representation learning technology represented by deep learning has received extensive attention. Representation learning aims to i...
Claims
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IPC IPC(8): G06F16/36G06F16/33G06F40/295G06F40/30G06N5/02
CPCG06F16/367G06F16/3344G06N5/022G06F40/30G06F40/205G06F40/284G06N3/045G06N5/02G06N20/00G06N7/01G06F40/137G06F40/295
Inventor 庞超王硕寰孙宇吴华王海峰
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD