Automatic extraction method of map reasoning rule

An automatic extraction and rule technology, applied in special data processing applications, instruments, unstructured text data retrieval, etc., can solve problems such as complex and long rules that cannot be extracted

Pending Publication Date: 2020-07-03
ZHEJIANG UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] In order to obtain graph inference rule data more efficiently, enhance the interpretability of extracted rules, and overcome the situation that complex and long rules cannot be extracted in traditional methods, this invention proposes an automatic extraction method for graph inference rules

Method used

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  • Automatic extraction method of map reasoning rule
  • Automatic extraction method of map reasoning rule
  • Automatic extraction method of map reasoning rule

Examples

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experiment example

[0091] There is the entity relationship information of the criminal character relationship graph in Table 1 below.

[0092] Table 1

[0093]

[0094] Now the method of the present invention is used to extract the rules related to the relationship r (associate in crime) in the graph. In order to more intuitively understand the relationship between entities in the graph and the steps of this method, the relationship between the knowledge graph is obtained from Table 1 as attached Figure 4 , the circular nodes represent entities, and the numbers on the lines represent the connections between entities.

[0095] According to the method of the present invention, the knowledge map relationship can now be constructed as follows: Figure 5 Several individuals of the two populations of , among them, the circular node represents the processing node, the hexagonal node represents the judgment node, the number in the hexagonal node represents the connection relationship represented b...

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Abstract

The invention discloses an automatic extraction method of a map reasoning rule, which comprises the following steps: 1) constructing a forward population and a reverse population by using map data andrelationship information of a rule to be extracted, each population comprising a certain number of primary individuals, and each individual comprising a plurality of randomly connected processing nodes and judgment nodes; 2) extracting a node chain from each individual; and 3) extracting rules through the map data and the node chain, calculating relevant indexes of the rules, and feeding back therelevant indexes to relevant individuals and nodes according to results. And 4) selecting individuals with higher fitness from the two populations of the generation as parent individuals to carry outrandom variation and population crossing on all the individuals to generate individuals of the next generation. And 5) repeatedly executing the above steps until a set target algebra is reached or nonew rule is generated after a certain algebra. According to the method, the rule meeting the requirements can be effectively extracted, and the rule has relatively good interpretability.

Description

technical field [0001] The invention belongs to the technical field of data mining and information processing, and in particular relates to an automatic extraction method of graph reasoning rules. Background technique [0002] With the rapid development of information technology, various industries have generated huge amounts of data, most of which are often invalid data and cannot generate more value, but relational data can obtain more market information through analysis and create more Much secondary value. In order to better store and analyze such relational data, knowledge graph technology came into being. Knowledge map is also called scientific knowledge map, which is called knowledge domain visualization or knowledge domain mapping map in the library and information industry. Carrier, excavating, analyzing, constructing, mapping and displaying knowledge and the relationship between them. [0003] A knowledge graph is a directed graph composed of entities and relati...

Claims

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Application Information

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IPC IPC(8): G06F16/34G06F16/36G06N3/00
CPCG06F16/34G06F16/367G06N3/006
Inventor 俞山青童天航甘燃陈晋音宣琦
Owner ZHEJIANG UNIV OF TECH
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