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Formal Models of Graph Transformation in Natural Language Processing (Dagstuhl Seminar 15122)
Umeå University.
University of Southern California, Information Sciences Institute.
Linköpings universitet, Institutionen för datavetenskap, Interaktiva och kognitiva system. Linköpings universitet, Tekniska fakulteten. (Natural Language Processing)ORCID-id: 0000-0002-2492-9872
2015 (Engelska)Ingår i: Dagstuhl Reports, ISSN 2192-5283, Vol. 5, nr 3, s. 143-161Artikel i tidskrift, Meeting abstract (Övrigt vetenskapligt) Published
Abstract [en]

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.

Ort, förlag, år, upplaga, sidor
2015. Vol. 5, nr 3, s. 143-161
Nyckelord [en]
natural language processing, graph transformation
Nationell ämneskategori
Språkteknologi (språkvetenskaplig databehandling)
Identifikatorer
URN: urn:nbn:se:liu:diva-124720DOI: 10.4230/DagRep.5.3.143OAI: oai:DiVA.org:liu-124720DiVA, id: diva2:902495
Tillgänglig från: 2016-02-11 Skapad: 2016-02-11 Senast uppdaterad: 2018-01-10

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Kuhlmann, Marco

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