The State of the Art in Graph-Based Pattern Matching

The task of searching for patterns in graph-structured data has applications in such diverse areas as computer vision, biology, electronics, computer aided design, social networks, and intelligence analysis. As such, work on graph-based pattern matching spans a wide range of research communities. Due to variations in graph characteristics and problem requirements, graph-based pattern matching is not a single problem, but a set of related problems. This paper presents a survey of existing work on graph-based pattern matching, describing variations among graph matching problems, general and specific solution approaches, evaluation techniques, and directions for further research. An emphasis is given to techniques that apply to general graphs with semantic characteristics. The survey also discusses techniques for graph mining, an extension of the graph matching problem.

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