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2002
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Exploiting Local Similarity for Indexing Paths in Graph-Structured Data

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Exploiting Local Similarity for Indexing Paths in Graph-Structured Data
XML and other semi-structured data may have partially specified or missing schema information, motivating the use of a structural summary which can be automatically computed from the data. These summaries also serve as indices for evaluating the complex path expressions common to XML and semi-structured query languages. However, to answer all path queries accurately, summaries must encode information about long, seldom-queried paths, leading to increased size and complexity with little added value. We introduce the A(k)-indices, a family of approximate structural summaries. They are based on the concept of k-bisimilarity, in which nodes are grouped based on local structure, i.e., the incoming paths of length up to k. The parameter k thus smoothly varies the level of detail (and accuracy) of the A(k)-index. For small values of k, the size of the index is substantially reduced. While smaller, the A(k) index is approximate, and we describe techniques for efficiently extracting exact answ...
Raghav Kaushik, Pradeep Shenoy, Philip Bohannon, E
Added 01 Nov 2009
Updated 01 Nov 2009
Type Conference
Year 2002
Where ICDE
Authors Raghav Kaushik, Pradeep Shenoy, Philip Bohannon, Ehud Gudes
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