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Set similarity-based sub-graph matching method in big graph database

A technology that integrates similarity and matching methods, applied in other database retrieval, other database query, electronic digital data processing, etc., can solve problems such as high query loss, achieve good pruning effect, and reduce the effect of search space

Inactive Publication Date: 2017-08-22
WUHAN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, these two methods usually cause high query loss, especially in the face of large graph databases

Method used

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  • Set similarity-based sub-graph matching method in big graph database
  • Set similarity-based sub-graph matching method in big graph database
  • Set similarity-based sub-graph matching method in big graph database

Examples

Experimental program
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Effect test

Embodiment

[0059] Embodiment: Find required papers from DBLP

[0060] The DBLP Computer Science Catalog provides a citation graph G such as figure 1 b, where the vertices represent the papers, and the edges represent the citation relationship between the papers. Each article contains a keyword set, and each keyword is given a weight to measure its importance in the article. In fact, a researcher will find papers from DBLP based on citation relationship and similarity of article content. For example, a researcher wants to find papers on subgraph matching that are cited by both papers on social networks and papers on protein interactions. In addition, the researcher needs papers in the study of protein interaction networks that are cited by articles in social networks. Such queries can be modeled as SMS 2 The query problem consists of finding matches from G in the query graph Q( figure 1 a) subgraph. Each paper in Q, i.e., a vertex, and its matching paper in G should have a similar s...

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PUM

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Abstract

The invention discloses a set similarity-based sub-graph matching method in a big graph database. The method comprises the following steps of 1) selecting an economic domination set from a plurality of domination sets of a query graph; 2) performing set similarity pruning: obtaining all candidate points of a query vertex by applying a set similarity pruning method; 3) performing structure-based pruning: performing the structure-based pruning on all the candidate points of the query vertex according to structure limitation of query graph Q isomorphism, and filtering the candidate points of the query vertex; and 4) performing domination set-based sub-graph matching. The invention provides an effective dual-graph pruning method, which comprises the set similarity pruning and the structure-based pruning; through the method, the query graph isomorphism can be retrieved; the vertex matching conditions of applying dynamic weighted set similarity are met; and the query efficiency is effectively improved.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a subgraph matching method based on set similarity in a large graph database. Background technique [0002] As a data structure, a graph can describe the connection between common things concisely and powerfully, so the data mining and management technology based on graph has an important position in both academic research and industrial application. In many real-world applications such as social networks, semantic networks, biological networks, etc., graph databases have been widely used as an important tool for modeling and querying complex graph data. Many scholars have extensively studied various queries on graphs, among which subgraph matching is a basic type of graph query. The mathematical basis of subgraph matching is subgraph isomorphism, a classic problem in graph theory, a well-known NP problem. Given a query graph Q and a large graph G, a typical subgraph matching...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/903G06F16/9024
Inventor 洪亮邹磊
Owner WUHAN UNIV
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