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Adaptive Processing of Top-k Queries in XML

Overview 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. This paper proposes an architecture and adaptive algorithms for efficiently computing top-k matches to XML queries.

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Publisher
AT&T Labs-Research
File Format
PDF
Date Published
Nov 3, 2008
Format
White Papers
Topics
XML

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