Query Processing in Graphical Data

Santosh Kumar Sahu, Mujeeb Rahaman


Graph data are becoming increasingly more ubiquitous in today’s networked world. Examples include social networks such as MySpace and Facebook as well as cell phone networks and blogs. The network routing across the Internet is another example of graph data, as is the hyperlinked structure of the World Wide Web (WWW). Bioinformatics, especially systems biology, deals with understanding interactions networks between various types of biomolecules, such as protein-protein interactions, metabolic networks, gene networks, and so on. Another example comes from semi-structured data, say in the form of XML documents. Given a graph query, it is desirable to retrieve graphs quickly from a large database via graph-based indices. We are using of frequent substructure as the basic indexing feature. Frequent substructures are ideal candidates since they explore the intrinsic characteristics of the data and are relatively stable to database updates. To reduce the size of index structure, we used techniques, size-increasing support discriminative fragments.


Keywords: Graph indexing, frequent fragments, discriminative fragments, gSpan, index construction

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DOI: https://doi.org/10.26483/ijarcs.v4i1.1460


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