An Edge-Based Framework for Fast Subgraph Matching in a Large Graph
7
Citation
15
Reference
10
Related Paper
Citation Trend
Keywords:
Subgraph isomorphism problem
Graph factorization
Factor-critical graph
Graph isomorphism
Distance-hereditary graph
Subgraph isomorphism problem
Graph isomorphism
Graph factorization
Distance-hereditary graph
Factor-critical graph
Graph traversal
Graph homomorphism
Cite
Citations (15)
Subgraph isomorphism problem
Graph factorization
Factor-critical graph
Graph isomorphism
Distance-hereditary graph
Cite
Citations (7)
Subgraph Matching is a fundamental problem in graph analysis, and is widely used in many application scenarios in biology, chemistry and social network. Given a data graph and a query graph, subgraph matching aims to compute all subgraphs of the data graph that are isomorphic to the query graph. The problem is computationally expensive as the core operation it depends on, known as subgraph isomorphism, is NP-complete. In recent years, graph is increasing extensively and it is hard to compute subgraph matching on massive graph data using existing serial algorithm. Meanwhile, there exist distributed solutions, but they are mostly limited to the case where the graphs are unlabelled. In response to this gap, we study the subgraph matching problem in the multi-core environment. From the algorithm level, we propose a multi-core parallel subgraph matching algorithm called MPMatch. From the research level, we explore the concurrent allocation of subgraph matching search space to approach load balancing. We conduct extensive empirical studies on real and synthetic graphs to demonstrate that our techniques improve the performance of serial subgraph matching algorithm via parallelization and well-developed load balancing schema.
Subgraph isomorphism problem
Factor-critical graph
Graph factorization
Distance-hereditary graph
Graph isomorphism
Cite
Citations (8)
Subgraph isomorphism problem
Factor-critical graph
Graph factorization
Distance-hereditary graph
Cite
Citations (23)
Isomorphic subgraphs finding is important in many real world applications. Being NP-hard problem, various approaches have been proposed by varying indexing, candidate generation, early pruning of unpromising regions, and graph traversal. While, recent research additionally emphasis on taking into account order of query or data graph vertices and compressing to make it best fit for subgraph isomorphism. However, subgraph isomorphism has not been evaluated deeply by summarized graph. Subgraph isomorphism performance can be improved by using summarized graphs with exactness. For this purpose, we evaluate subgraph isomorphism performance on a single large graph by using backtracking algorithm. We extend Ullman algorithm for original and summarized graph. We evaluate subgraph isomorphism performance on both original and summarized version of graph through experiments on publically available real world graph.
Subgraph isomorphism problem
Graph isomorphism
Graph homomorphism
Graph factorization
Factor-critical graph
Distance-hereditary graph
Graph property
Graph automorphism
Cite
Citations (0)
Subgraph query in graph set returns data graph containing query graph.When the query graph and data graph both are uncertain,this paper proposes a definition of subgraph isomorphism between uncertain graphs and a definition of α-β subgraph isomorphism matching.Expectation subgraph isomorphism between uncertain graphs is a direct extension of subgraph isomorphism between deterministic graphs on probability graph model.There are two parameters α and β which are the thresholds to restrict quality of matching between query graph and data graph.This paper elaborates features of α-β subgraph isomorphism matching in detail,analyzes the differences between it and expectation subgraph isomorphism,meanwhile proposes α-β subgraph isomorphism matching decision algorithm.
Subgraph isomorphism problem
Graph isomorphism
Graph factorization
Distance-hereditary graph
Factor-critical graph
Graph automorphism
Graph homomorphism
Graph property
Cite
Citations (0)
Given a query graph, subgraph matching is the process of finding all the isomorphic graphs over a large data graph. Subgraph is one of the fundamental steps of many graph-based applications including recommendation system, information retrieval, social network analysis, etc. In this paper, we investigate the problem of subgraph matching over power grid knowledge graph. Since knowledge graph is a modelled as a directed, labelled, and multiple edges graph, it brings new challenges for the subgraph matching on knowledge graph. One challenge is that subgraph matching candidate calculation complexity increases with edges increase. Another challenge is that the search space of isomorphic subgraphs for a given region is huge, which needs more system resources to prune the unpromising graph candidates. To address these challenges, we propose subgraph index to accelerate the matching processing of subgraph que-ry. We use domain-specific information to construct index of power grid knowledge and maintain a small portion of search candidates in the search space. Experimental studies on real knowledge graph and synthetic graphs demonstrate that the proposed techniques are efficient compared with counterparts.
Subgraph isomorphism problem
Factor-critical graph
Graph factorization
Distance-hereditary graph
Block graph
Null graph
Cite
Citations (1)
Subgraph isomorphism problem
Graph factorization
Factor-critical graph
Graph isomorphism
Distance-hereditary graph
Cite
Citations (2)
Subgraph isomorphism problem
Graph isomorphism
Factor-critical graph
Isomorphism (crystallography)
Graph factorization
Distance-hereditary graph
Cite
Citations (0)
The subgraph isomorphism problem is the problem of whether one graph is contained in another graph, given two graphs. An enormous calculation cost is necessary for this problem when large quantities of graphs are handled because it is NP complete. Messmer et al. propose the algorithm to solve this problem efficiently based on graph decomposition. We improve the Messmer’s approach so that connected graphs are formed in the decomposition of each graph and information produced by graph decomposition is used in subgraph isomorphism detection. Keyword Subgraph isomorphism,Graph decomposition,Graph matching
Subgraph isomorphism problem
Graph isomorphism
Distance-hereditary graph
Graph factorization
Factor-critical graph
Graph homomorphism
Cograph
Graph property
Modular decomposition
Graph automorphism
Block graph
Cite
Citations (0)