To rectify these problems, this article 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.

Feb 1, 2018 · For each experiment, we ran 4 different matching strategies on the pattern and data graphs: limited simulation, limited simulation without node label, limited simulation without edge label, and graph simulation.

We contend that strong simulation provides a promising model for graph pattern matching in emerging applications. Indeed, (1) in contrast to subgraph isomorphism,

May 13, 2013 · To model varying abstraction levels in the data, we work with partially ordered alphabets and compute simulation relations rather than equivalence relations. In particular, vertices and edges are labelled with elements from a pair of …

Dec 31, 2011 · 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.

Graph patterns, pattern composites and graph pattern matching algorithms are used to define and identify potential model components. Model composite structures are represented by hypergraphs according to which simulation models are generated using model components as building blocks.

Graph pattern matching is a fundamental problem in analyzing attributed graphs, that is to search the matches of a given query graph in a large data graph. However, existing algorithms either encounter with the performance issues or cannot capture reasonable matches.

Jun 14, 2020 · To rectify these problems, this article proposes a notion of strong simulation, a revision of graph simulation for graph pattern matching.

Nov 21, 2022 · To deal with this issue, we introduce a new graph pattern matching (GPM) method, called partial simulation, capable of retrieving matches despite missing parts of the pattern graph, such as vertices and/or edges.

Sep 1, 2022 · In this paper, we propose Bounded Dual Simulation (BDSim) as a new relaxed model for a scalable evaluation of GPM in massive graphs. BDSim captures more semantic similarities compared to graph simulation, dual simulation, and even strong simulation.