Abstract
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.
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Yilmaz, F., Demirci, M.F. (2011). Indexing Tree Structures through Caterpillar Decomposition. In: Heyden, A., Kahl, F. (eds) Image Analysis. SCIA 2011. Lecture Notes in Computer Science, vol 6688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21227-7_64
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DOI: https://doi.org/10.1007/978-3-642-21227-7_64
Publisher Name: Springer, Berlin, Heidelberg
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