DagRep.5.3.143.pdf
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Formal Models of Graph Transformation in Natural Language Processing (Dagstuhl Seminar 15122)
Authors and all authors of the abstracts in this report
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Dagstuhl Reports, Volume 5, Issue 3
Volume: Dagstuhl Reports, Volume 5
Journal: Dagstuhl Reports (DagRep) - License:
Creative Commons Attribution 3.0 Unported license
- Publication Date: 2015-09-18
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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)
https://doi.org/10.4230/DagRep.5.3.143
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.
Subject Classification
Keywords
- Automata theory
- Graph transformation
- Natural language processing
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