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Research on the Top-Down Parsing Method for Context-Sensitive Graph Grammars

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 30 Nov 2015Publisher:Public Library of Science (PLoS)Journal:PLOS ONE, volume 10, page e0142776 (eissn: 1932-6203, Copyright policy )
Authors: Yi Wang; Yi Wang; Han Ding; XiaoQin Zeng;

doi: 10.1371/journal.pone.0142776

pmid: 26618493

pmc: PMC4664237

Research on the Top-Down Parsing Method for Context-Sensitive Graph Grammars

Abstract

The parsing problem is one of the key problems of graph grammars. The typical parsing algorithm uses the bottom-up method. The time-complexity of this method is high, and it is difficult to apply. In order to reduce the time-complexity, this paper uses the top-down method for parsing. This method avoids the subgraph isomorphism judgment and selects the productions specifically, so that the time-complexity is greatly reduced.

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Science, Q, R, Medicine, Mathematical Concepts, Research Article

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citations
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!
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Average
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