Del 0 - Lecture Notes in Computer Science

Finite-State Methods and Natural Language Processing

8th International Workshop, FSMNLP 2009, Pretoria, South Africa, July 21-24, 2009, Revised Selected Papers

Häftad, Engelska, 2010

AvAnssi Yli-Jyrä,Andras Kornai,Jacques Sakarovitch,Bruce Watson

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This book constitutes the refereed proceedings of the 8th International Workshop on the Finite-State-Methods and Natural Language Processing, FSMNLP 2009. The workshop was held at the University of Pretoria, South Africa on July 2009. In total 21 papers were submitted and of those papers 13 were accepted as regular papers and a further 6 as extended abstracts. The papers are devoted to computational morphology, natural language processing, finite-state methods, automata, and related formal language theory.

Produktinformation

Utgivningsdatum2010-08-05
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor147
FörlagSpringer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN9783642146831

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Tutorials.- Learning Finite State Machines.- Special Theme Tutorials.- Developing Computational Morphology for Low- and Middle-Density Languages.- Invited Papers.- fsm2 – A Scripting Language Interpreter for Manipulating Weighted Finite-State Automata.- Selected Operations and Applications of n-Tape Weighted Finite-State Machines.- OpenFst.- Special Theme Invited Talks.- Morphological Analysis of Tone Marked Kinyarwanda Text.- Regular Papers.- Minimizing Weighted Tree Grammars Using Simulation.- Compositions of Top-Down Tree Transducers with ?-Rules.- Reducing Nondeterministic Finite Automata with SAT Solvers.- Joining Composition and Trimming of Finite-State Transducers.- Special Theme Extended Abstracts.- Porting Basque Morphological Grammars to foma, an Open-Source Tool.- Describing Georgian Morphology with a Finite-State System.- Finite State Morphology of the Nguni Language Cluster: Modelling and Implementation Issues.- A Finite State Approach to Setswana Verb Morphology.- Competition Announcements.- Zulu: An Interactive Learning Competition.