Computer Science – Databases
Scientific paper
2011-12-31
Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 4, pp. 310-321 (2011)
Computer Science
Databases
VLDB2012
Scientific paper
Graph pattern matching is often defined in terms of subgraph isomorphism, an NP-complete problem. To lower its complexity, various extensions of graph simulation have been considered instead. These extensions allow pattern matching to be conducted in cubic-time. However, they fall short of capturing the topology of data graphs, i.e., graphs may have a structure drastically different from pattern graphs they match, and the matches found are often too large to understand and analyze. To rectify these problems, this paper proposes a notion of strong simulation, a revision of graph simulation, for graph pattern matching. (1) We identify a set of criteria for preserving the topology of graphs matched. We show that strong simulation preserves the topology of data graphs and finds a bounded number of matches. (2) We show that strong simulation retains the same complexity as earlier extensions of simulation, by providing a cubic-time algorithm for computing strong simulation. (3) We present the locality property of strong simulation, which allows us to effectively conduct pattern matching on distributed graphs. (4) We experimentally verify the effectiveness and efficiency of these algorithms, using real-life data and synthetic data.
Cao Yang
Fan Wenfei
Huai Jinpeng
Ma Shuai
Wo Tianyu
No associations
LandOfFree
Capturing Topology in Graph Pattern Matching does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Capturing Topology in Graph Pattern Matching, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Capturing Topology in Graph Pattern Matching will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-672813