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Approximating Parikh Images for Generating Deterministic Graph Parsers
Umeå University, Faculty of Science and Technology, Department of Computing Science. (Foundations of Language Processing)ORCID iD: 0000-0001-7349-7693
2016 (English)In: 7th International Workshop on Graph Computation Models / [ed] Barbara König, 2016Conference paper, Published paper (Refereed)
Abstract [en]

The Parikh image of a word abstracts from the order of its letters. Parikh's famous theorem states that the set of Parikh images of a context-free string language forms a semilinear set that can be effectively computed from its grammar. In this paper we study the computation of Parikh images for graph grammars defined by contextual hyperedge replacement (CHR). Our motivation is to generate efficient predictive top-down (PTD) parsers for a subclass of CHR grammars. We illustrate this by describing the subtask that identifies the nodes of the input graph that parsing starts with.

Place, publisher, year, edition, pages
2016.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:umu:diva-121079OAI: oai:DiVA.org:umu-121079DiVA: diva2:930933
Conference
7th International Workshop on Graph Computation Models
Available from: 2016-05-25 Created: 2016-05-25 Last updated: 2016-05-25

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
  • rtf