Modeling graph languages with grammars extracted via tree decompositions

Bevan Keeley Jones, Sharon Goldwater, Mark Johnson

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Abstract

Work on probabilistic models of natural language tends to focus on strings and trees, but there is increasing interest in more general graph-shaped structures since they seem to be better suited for representing natural language semantics, ontologies, or other varieties of knowledge structures. However, while there are relatively simple approaches to defining generative models over strings and trees, it has proven more challenging for more general graphs. This paper describes a natural generalization of the n-gram to graphs, making use of Hyperedge Replacement Grammars to define generative models of graph languages.
Original languageEnglish
Title of host publicationFSMNLP 2013
Subtitle of host publicationProceedings of the 11th International Conference on Finite State Methods and Natural Language Processing
Place of PublicationStroudsburg, PA
PublisherAssociation for Computational Linguistics
Pages54-62
Number of pages9
Publication statusPublished - 2013
EventInternational Conference on Finite State Methods and Natural Language Processing (11th : 2013) - St Andrews, Scotland
Duration: 15 Jul 201317 Jul 2013

Conference

ConferenceInternational Conference on Finite State Methods and Natural Language Processing (11th : 2013)
CitySt Andrews, Scotland
Period15/07/1317/07/13

Fingerprint Dive into the research topics of 'Modeling graph languages with grammars extracted via tree decompositions'. Together they form a unique fingerprint.

  • Cite this

    Jones, B. K., Goldwater, S., & Johnson, M. (2013). Modeling graph languages with grammars extracted via tree decompositions. In FSMNLP 2013: Proceedings of the 11th International Conference on Finite State Methods and Natural Language Processing (pp. 54-62). Stroudsburg, PA: Association for Computational Linguistics.