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Documents authored by Knight, Kevin

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DOI: 10.4230/DagRep.5.3.143
Formal Models of Graph Transformation in Natural Language Processing (Dagstuhl Seminar 15122)

Authors: Frank Drewes, Kevin Knight, and Marco Kuhlmann

Published in: Dagstuhl Reports, Volume 5, Issue 3 (2015)

Abstract
In natural language processing (NLP) there is an increasing interest in formal models for processing graphs rather than more restricted structures such as strings or trees. Such models of graph transformation have previously been studied and applied in various other areas of computer science, including formal language theory, term rewriting, theory and implementation of programming languages, concurrent processes, and software engineering. However, few researchers from NLP are familiar with this work, and at the same time, few researchers from the theory of graph transformation are aware of the specific desiderata, possibilities and challenges that one faces when applying the theory of graph transformation to NLP problems. The Dagstuhl Seminar 15122 "Formal Models of Graph Transformation in Natural Language Processing" brought researchers from the two areas together. It initiated an interdisciplinary exchange about existing work, open problems, and interesting applications.
Cite as

Frank Drewes, Kevin Knight, and Marco Kuhlmann. Formal Models of Graph Transformation in Natural Language Processing (Dagstuhl Seminar 15122). In Dagstuhl Reports, Volume 5, Issue 3, pp. 143-161, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

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@Article{drewes_et_al:DagRep.5.3.143,
  author =	{Drewes, Frank and Knight, Kevin and Kuhlmann, Marco},
  title =	{{Formal Models of Graph Transformation in Natural Language Processing (Dagstuhl Seminar 15122)}},
  pages =	{143--161},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2015},
  volume =	{5},
  number =	{3},
  editor =	{Drewes, Frank and Knight, Kevin and Kuhlmann, Marco},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.5.3.143},
  URN =		{urn:nbn:de:0030-drops-53484},
  doi =		{10.4230/DagRep.5.3.143},
  annote =	{Keywords: Automata theory, Graph transformation, Natural language processing}
}
Document
DOI: 10.4230/DagRep.4.2.1
Statistical Techniques for Translating to Morphologically Rich Languages (Dagstuhl Seminar 14061)

Authors: Alexander M. Fraser, Kevin Knight, Philipp Koehn, Helmut Schmid, and Hans Uszkoreit

Published in: Dagstuhl Reports, Volume 4, Issue 2 (2014)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 14061 "Statistical Techniques for Translating to Morphologically Rich Languages". The seminar took place in February 2014. The purpose of the seminar was to allow disparate communities working on problems related to morphologically rich languages to meet to discuss an important research problem, translation to morphologically rich languages. While statistical techniques for machine translation have made significant progress in the last 20 years, results for translating to morphologically rich languages are still mixed versus previous generation rule-based systems, so this is a critical and timely topic. Current research in statistical techniques for translating to morphologically rich languages varies greatly in the amount of linguistic knowledge used and the form of this linguistic knowledge. This varies most strongly by target language, for instance the resources currently used for translating to Czech are very different from those used for translating to German. The seminar met a pressing need to discuss the issues involved in these translation tasks in a more broad venue than the ACL Workshops on Machine Translation, which are primarily attended by statistical machine translation researchers. The report describes the introductory material presented to the group, the organization of break-out discussion groups by topic, and the results of the seminar.
Cite as

Alexander M. Fraser, Kevin Knight, Philipp Koehn, Helmut Schmid, and Hans Uszkoreit. Statistical Techniques for Translating to Morphologically Rich Languages (Dagstuhl Seminar 14061). In Dagstuhl Reports, Volume 4, Issue 2, pp. 1-16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

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@Article{fraser_et_al:DagRep.4.2.1,
  author =	{Fraser, Alexander M. and Knight, Kevin and Koehn, Philipp and Schmid, Helmut and Uszkoreit, Hans},
  title =	{{Statistical Techniques for Translating to Morphologically Rich Languages (Dagstuhl Seminar 14061)}},
  pages =	{1--16},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2014},
  volume =	{4},
  number =	{2},
  editor =	{Fraser, Alexander M. and Knight, Kevin and Koehn, Philipp and Schmid, Helmut and Uszkoreit, Hans},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.4.2.1},
  URN =		{urn:nbn:de:0030-drops-45420},
  doi =		{10.4230/DagRep.4.2.1},
  annote =	{Keywords: Machine Translation, Statistical Machine Translation, Syntactic Parsing, Morphology, Machine Learning, Morphologically Rich Languages}
}
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