Extended Multi Bottom-Up Tree Transducers View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2008

AUTHORS

Joost Engelfriet , Eric Lilin , Andreas Maletti

ABSTRACT

Extended multi bottom-up tree transducers are defined and investigated. They are an extension of multi bottom-up tree transducers by arbitrary, not just shallow, left-hand sides of rules; this includes rules that do not consume input. It is shown that such transducers can compute any transformation that is computed by a linear extended top-down tree transducer. Moreover, the classical composition results for bottom-up tree transducers are generalized to extended multi bottom-up tree transducers. Finally, a characterization in terms of extended top-down tree transducers is presented. More... »

PAGES

289-300

References to SciGraph publications

  • 1975-06. Bottom-up and top-down tree transformations— a comparison in MATHEMATICAL SYSTEMS THEORY
  • 1981. Proprietes de cloture d'une extension de transducteurs d'arbres deterministes in CAAP '81
  • 1976-12. Top-down tree transducers with regular look-ahead in MATHEMATICAL SYSTEMS THEORY
  • 1970-09. Mappings and grammars on trees in MATHEMATICAL SYSTEMS THEORY
  • 1998. Benefits of Tree Transducers for Optimizing Functional Programs in FOUNDATIONS OF SOFTWARE TECHNOLOGY AND THEORETICAL COMPUTER SCIENCE
  • 2007. Syntax-Directed Translations and Quasi-alphabetic Tree Bimorphisms in IMPLEMENTATION AND APPLICATION OF AUTOMATA
  • 1988-05. Composition and evaluation of attribute coupled grammars in ACTA INFORMATICA
  • 1997. Tree Languages in HANDBOOK OF FORMAL LANGUAGES
  • 2005. An Overview of Probabilistic Tree Transducers for Natural Language Processing in COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING
  • Book

    TITLE

    Developments in Language Theory

    ISBN

    978-3-540-85779-2
    978-3-540-85780-8

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-540-85780-8_23

    DOI

    http://dx.doi.org/10.1007/978-3-540-85780-8_23

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1045791096


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