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Published Articles >> Table of Contents >> Abstract
21st International Conference on Data Engineering (ICDE'05)
pp. 162-173
Adaptive Processing of Top-k Queries in XML
Amélie Marian, Columbia University
Sihem Amer-Yahia, AT&T Labs-Research
Nick Koudas, AT&T Labs-Research
Divesh Srivastava, AT&T Labs-Research
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDE.2005.18
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| Abstract |
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The ability to compute top-k matches to XML queries is
gaining importance due to the increasing number of large
XML repositories. The efficiency of top-k query evaluation
relies on using scores to prune irrelevant answers as early
as possible in the evaluation process. In this context, evaluating
the same query plan for all answers might be too rigid
because, at any time in the evaluation, answers have gone
through the same number and sequence of operations, which
limits the speed at which scores grow. Therefore, adaptive
query processing that permits different plans for different
partial matches and maximizes the best scores is more appropriate.
In this paper, we propose an architecture and
adaptive algorithms for efficiently computing top-k matches
to XML queries. Our techniques can be used to evaluate
both exact and approximate matches where approximation
is defined by relaxing XPath axes. In order to compute the
scores of query answers, we extend the traditional tf*idf
measure to account for document structure. We conduct extensive
experiments on a variety of benchmark data and
queries, and demonstrate the usefulness of the adaptive approach
for computing top-k queries in XML.
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 Additional Information
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Citation:
Amélie Marian, Sihem Amer-Yahia, Nick Koudas, Divesh Srivastava,
"Adaptive Processing of Top-k Queries in XML,"
icde,
pp. 162-173,
21st International Conference on Data Engineering (ICDE'05),
2005
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