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Lazy DFA filter based on stream index for XML data streams

Authors: Li-li Zhang; He-ji Zhao; Wei-jian Xia;

Lazy DFA filter based on stream index for XML data streams

Abstract

Lazy DFA (Deterministic Finite Automata) is an effective and scalable filtering system of XML documents, but it must parse every element of every XML document. In this paper, we put forward a new method to filter XML documents, called stream index which stores index information of every XML document. By using index information, the application can skip worthless elements and their sub-elements. Therefore, the elements which match elements' position can be quickly located, and to the largest extent, eliminating elements that are not guaranteed to be part of any match is able to avoid an amount of redundant processing. Experiments show that the proposed method is extensible, and can improve the efficiency indeed.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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