Graphs provide effective data structures modeling complex relations and schemaless data such as images, XML documents, circuits, compounds, and proteins. Given a query graph, efficiently finding all database graphs in which the query is a subgraph is an important problem raising in different domains. In this paper, we propose a new method for indexing tree structures based on a graph-theoretic concept called caterpillar decomposition and discuss its advantages over two previous indexing algorithms. Experimental evaluation of the proposed framework including the comparison with the previous approaches demonstrates the efficacy of the overall approach. © 2011 Springer-Verlag.
CITATION STYLE
Yilmaz, F., & Demirci, M. F. (2011). Indexing tree structures through caterpillar decomposition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6688 LNCS, pp. 687–696). https://doi.org/10.1007/978-3-642-21227-7_64
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