Sub-graph matching device and sub-graph matching method

Abstract

The invention discloses a sub-graph matching device, which is used for finding out a sub-graph matched with a loop graph in a large-scale graph. The device comprises a spanning tree module, a matching module, a judging module and a gathering module. A spanning tree of the loop graph is found by the spanning tree module according to a minimum spanning tree algorithm; the spanning tree matching is carried out on a data graph by the matching module from bottom to top to find a tree Li (i>=1) matched with the spanning tree; whether the sum of a grading function value of the tree Li and the missing edge number is larger than or equal to a preset value or not is judged by the judging module, if so, whether the tree Li can be expanded into the loop graph or not is judged by the judging module; and the gathering module can be used for outputting the previous fixed value number of matching graphs in a set V when the sum of the grading function value of the tree Li and the missing edge number is larger than or equal to the preset value.

Description

technical field [0001] The invention relates to data search technology, in particular to a subgraph matching device and a subgraph matching method for performing subgraph matching on a large data graph. Background technique [0002] With the development of web technologies and new data management and storage technologies, graph-structured data is becoming more and more common. The graph structure can clearly express the complex relationship between objects. Many applications need to deal with graph-structured data, such as semantic web [1], protein interaction network in bioinformatics [2] and social network in social science, etc. These applications require efficient storage and analysis of single or multiple large graph data. [0003] When analyzing graph data, it is often necessary to query the graph. Unlike the query in the relational database, the query of the graph is generally based on the structure of the graph. Queries related to graphs can be roughly divided int...

AI Technical Summary

Problems solved by technology

In the face of large data graphs, the matching result set of a given query is very large, so it will be very time-consuming to use the existing subgraph matching algorithm to find all the matches, and then obtain the top-k results by sorting

[0006] 2. The existing top-k connection algorithm can be directly used to solve the top-k subgraph matching, but the analysis and experiments of the algorithm show that this algorithm does not have good performance, especially for large data graphs

Existing top-k subtree matching algorithms cannot be directly used to solve top-k subgraph matching

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