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Knowledge graph construction method and system and information query method and system

A technology of knowledge graph and construction method, which is applied in digital data information retrieval, relational database, structured data retrieval, etc. It can solve the problems of knowledge graph maintenance and query difficulties, and the inability to further mine relationships, etc., to achieve the effect of easy analysis and mining

Pending Publication Date: 2021-05-07
新华智云科技有限公司 +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, knowledge graphs generally use graph databases for data storage. In most graph databases, the head and tail nodes will store edge information. When there are too many nodes entering / exiting edges in the knowledge graph, the subsequent knowledge graph Difficult to maintain and query
[0004] Record the nodes with the number of incoming / outgoing edges exceeding the preset number threshold (such as 10000) as super large nodes, such as people and regions as entities, and hometown as a relationship, provinces / cities may become super large nodes; People and dynasties are entities, and the era they live in is a relationship. Dynasties or historical periods may become super-large nodes; in view of the above situation, in order to avoid super-large nodes, those skilled in the art often use attributes to store them. This method will give up the relationship analysis. Potential value, making it impossible to further explore the potential relationship between entities

Method used

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  • Knowledge graph construction method and system and information query method and system
  • Knowledge graph construction method and system and information query method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0043] Embodiment 1. A method for constructing a knowledge map. The obtained knowledge map includes the above-mentioned basic knowledge map and also includes an abstract concept map, that is, a method for constructing an abstract concept map based on the existing construction method, specifically including the following steps:

[0044] Obtain several tags and obtain the association relationship between each tag;

[0045] Taking the labels as nodes and the association relationship as edges, a directed graph is constructed as an abstract concept graph.

[0046] Obtain industry data in the target field, construct a basic knowledge graph based on the industry data and the tags, the nodes of the initial graph are entities, the edges are relationships between entities, and there are corresponding Label.

[0047] Those skilled in the art can obtain industry data in the target field, and construct a basic knowledge map according to any of the existing disclosed construction methods, ...

Embodiment 2

[0067] Embodiment 2, a system for building a knowledge map, which includes a first building block and a second building block;

[0068] The first building block is used to build a basic knowledge graph;

[0069] The second building block includes an acquisition unit and a construction unit;

[0070] The obtaining unit is used to obtain several tags, and is also used to obtain the association relationship between the tags;

[0071] The construction unit is configured to use the label as a node and the association relationship as an edge to construct a directed graph as an abstract concept graph.

[0072] This embodiment is an embodiment of the device corresponding to Embodiment 1. Since it is basically similar to Embodiment 1, the description is relatively simple. For relevant details, please refer to the description of Embodiment 1.

Embodiment 3

[0073] Embodiment 3. An information query method based on the knowledge graph constructed in Embodiment 1, which includes a method for performing associated query based on the basic knowledge graph, and also includes an associated extended query based on the abstract concept graph;

[0074] The associated extended query method includes the following steps:

[0075] Obtain label query request;

[0076] Based on the tag query request, the abstract concept map constructed in embodiment 1 is used for path query to obtain the corresponding tag association path (this path is not affected by the direction of the relationship);

[0077] This embodiment discovers and analyzes the potential relationship between tags through the abstract concept map, so as to reflect the potential relationship between entities with corresponding tags, so as to further optimize the existing relationship query based on the knowledge map, and make full use of the relationship between entities. Relationship...

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PUM

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Abstract

The invention discloses a knowledge graph construction method and system and an information query method and system.The construction method comprises a method for constructing an abstract concept graph and specifically comprises the following steps that a plurality of labels are obtained, and the incidence relation between the labels is obtained; and a directed graph is constructed as an abstract concept graph by taking the label as a node and the incidence relation as an edge. According to the method, through the design of the abstract concept graph, the generation of oversized nodes in the basic knowledge graph can be avoided, the interrupted relationship between the nodes in the basic knowledge graph can be made up through the relationship of the labels in the abstract concept graph, and the subsequent analysis and mining of the potential relationship between entities based on the relationship between the labels are facilitated.

Description

technical field [0001] The present invention relates to the field of information processing, in particular to a method and system for constructing a knowledge map, and an information query method and system. Background technique [0002] The storage form of information in the knowledge map mainly includes attributes, edges, labels, etc., among which attributes and edges are the basic elements of the graph, and labels are special attributes, which are usually stored in the form of multi-values ​​and are mainly used for abstract descriptions of entities. It is convenient for subsequent classification queries. [0003] At present, knowledge graphs generally use graph databases for data storage. In most graph databases, the head and tail nodes will store edge information. When there are too many nodes entering / exiting edges in the knowledge graph, the subsequent knowledge graph Maintenance and query are more difficult. [0004] Record the nodes with the number of incoming / outg...

Claims

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Application Information

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IPC IPC(8): G06F16/28G06F16/245G06F40/295
CPCG06F16/288G06F16/245G06F40/295
Inventor 杨丛聿仇应俊
Owner 新华智云科技有限公司