Literature entity relationship discovery method and system based on knowledge graph

A technology of entity relationship and knowledge graph, which is applied to the discovery method of document entity relationship and the system field where this method is applied, can solve problems such as low efficiency, low accuracy, and time-consuming and energy-consuming, and achieve large information tolerance and accelerated development The effect of the process

Active Publication Date: 2019-08-30
苏州无常师教育科技有限公司
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  • Literature entity relationship discovery method and system based on knowledge graph
  • Literature entity relationship discovery method and system based on knowledge graph
  • Literature entity relationship discovery method and system based on knowledge graph

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[0040] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention clearer and clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0041] Such as figure 1 Shown, a kind of document entity relation discovery method based on knowledge graph of the present invention, it comprises the following steps:

[0042] a. Construct a knowledge map according to the entities in the document content and the relationship between entities;

[0043] b. extracting the RDF data in the knowledge graph, and performing vectorization processing on the RDF data to obtain vector data;

[0044] c. According to the association relationship of the vector data, the original entity relationship vector group and...

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Abstract

The invention discloses a literature entity relationship discovery method and system based on a knowledge graph. The method comprises the following steps of constructing the knowledge graph accordingto the entities in the literature contents and the relationships among the entities; extracting the RDF data in the knowledge graph, and performing vectorization processing on the RDF data to obtain the vector data; obtaining a native entity relationship vector group and a non-connected entity relationship vector group according to the association relationship of the vector data; carrying out thevector matching degree calculation on the unconnected entity relationship vector groups, and screening out the unconnected entity relationship vector groups with the vector matching degrees greater than a preset threshold value, or sorting the unconnected entity relationship vector groups according to the vector matching degrees obtained through calculation. According to the method, the knowledgegraph is constructed by taking the entity in the literature content as the granularity; and the entity relationship matching is carried out through the vector calculation based on the knowledge graph,and the potential entity relationships among literature contents can be deeply mined, so that an innovative research method is provided to find the potential knowledge which is not found by human beings, and the development process of human science is accelerated.

Description

technical field [0001] The invention relates to the technical fields of information science and knowledge engineering, in particular to a method for discovering a document entity relationship based on a knowledge map and a system for applying the method. Background technique [0002] In the vast ocean in the academic field, there are many potential knowledge relationships or knowledge contents buried in the literature that have not yet been tapped. This is also the content of the work that scholars search for inspiration through a large number of literature reviews. This is the process of knowledge discovery. [0003] Document-based knowledge discovery, a more precise term is "knowledge discovery based on non-related documents", which was first proposed by Professor Swanson in 1986, and its meaning refers to: "Discovering some knowledge fragments from published non-related documents The implicit connection between them, and on this basis, scientific hypotheses or conjectures...

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Application Information

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IPC IPC(8): G06F16/28G06F16/36G06F16/33G06F17/27
CPCG06F16/288G06F16/367G06F16/3344G06F40/279G06F40/30Y02A40/81
Inventor 刘源
Owner 苏州无常师教育科技有限公司
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