CALL FOR PAPERS: Finite-State Methods and Natural Language Processing 2008

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        Finite-State Methods and Natural Language Processing
                                  FSMNLP 2008
                       Seventh International Workshop

                      SECOND  CALL  FOR  PAPERS 
  
                     11-12 September 2008, Ispra, Italy
      
        
                    http://langtech.jrc.it/FSMNLP2008
 
                   contact: fsmnlp2008 [ad] jrc [dot] it

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This year FSMNLP is merged with the FASTAR 
(Finite Automata Systems - Theoretical and Applied Research) 
workshop (http://www.fastar.org).


AIM AND SCOPE

The aim of the FSMNLP 2008 is to bring together members of the
research and industrial community working on finite-state
based models in language technology, computational linguistics,
web mining, linguistics, and cognitive science or on related 
theory and methods in fields such as computer science and mathematics.
The workshop will be a forum for researchers and practicioners working

  * on NLP applications,
  * on the theoretical and implementation aspects, or
  * on their combination.

The special theme of FSMNLP 2008 centers around high performance
finite-state devices in large-scale natural language text processing systems
and applications. We invite in particular novel high-quality papers related 
to the topics including:
   
  * practices and experience in deployment of finite-state techniques 
     in real-world applications processing massive amount of natural language data
  * industrial-strength finite-state pattern engines for information retrieval, 
     information extraction and related text-mining tasks
  * scalability issues in FS-based large-scale text processing systems
  * efficient finite-state methods in search engines
  * implementation, construction, compression and processing techniques for huge finite-state
     devices and networks
  * novel application and efficiency-oriented finite-state paradigms (compilation and processing),
     e.g., finite-state devices with rich label annotatations, unification-based finite-state devices
  * comparative studies of time and space efficient finite-state methods (vs. other techniques)
     utilized in NLP applications
  * novel appllication areas for finite-state devices in text processing 
     and information management systems
  * design patterns for implementing finite-state devices and toolkits 

We also invite submissions that are related to the traditional FSMNLP themes
including but not limited to:

1. NLP applications and linguistic aspects of finite-state methods

The topic includes but is not restricted to:

  * speech, sign language, phonology, hyphenation, prosody,
  * scripts, text normalization, segmentation, tokenization, indexing,
  * morphology, stemming, lemmatisation, information retrieval, web mining, spelling correction, 
  * syntax, POS tagging, partial parsing, disambiguation, information extraction, question answering 
  * machine translation, translation memories, glossing, dialect adaptation,
  * annotated corpora and treebanks, semi-automatic annotation, error mining, searching

2. Finite-state models of language

With this more focused topic (inside 1) we invite papers on aspects
that motivate sufficiency of finite-state methods or their subsets for
capturing various requirements of natural language processing. The
topic includes but is not restricted to:

  * performance, linguistic applicability, finite-state hypotheses
  * Zipf's law and coverage, model checking against finite corpora
  * regular approximations under parameterized complexity, limitations and definitions of relevant
     complexities such as ambiguity, recursion, crossings, rule applications, constraint violations,
     reduplication, exponents, discontinuity, path-width, and induction depth
  * similarity inferences, dissimilation, segmental length, counter-freeness, asynchronous machines
  * garden-path sentences, deterministic parsing, expected parses, Markov chains
  * incremental parsing, uncertainty, reliability/variance in stochastic parsing, 
     linear sequential machines

3. Practices for building lexical transducers for the world's languages.

The topic accounts for usability of finite-state methods in NLP. It
includes but is not restricted to:

  * required user training and consultation, learning curve of non-specialists
  * questionnaires, discovery methods, adaptive computer-aided glossing and interlinearization
  * example-based grammars, unsupervised learning, semi-automatic learning, user-driven learning
     (see topic 5 too)
  * low literacy level and restricted availability of training data, writing systems/phonology 
     under development, new non-Roman scripts, endangered languages
  * linguist's workbenches, stealth-to-wealth parser development
  * experiences of using existing tools (e.g. TWOL) for computational morphology and phonology

4. Specification and implementation of sets, relations and
multiplicities in NLP using finite state devices

The topic includes but is not restricted to:

  * regular rule formalisms, grammar systems, expressions, operations, closure properties,
     complexities
  * algorithms for compilation, approximation, manipulation, optimization, 
     and lazy evaluation of finite machines
  * finite string and tree automata, transducers, morphisms and bimorphisms
  * weights, registers, multiple tapes, alphabets, state covers and partitions, representations
  * locality, constraint propagation, star-free languages, data vs. query complexity
  * logical specification, MSO(SLR,matches), FO(Str,<), LTL, generalized restriction, local grammars
  * multi-tape automata, same-length relations and partition-based morphology, Semitic morphology
  * autosegmental phonology, shuffle, trajectories, synchronization, segmental anchoring,
     alignment constraints, syllable structure, partial-order reductions
  * varieties of regular languages and relations, 
     descriptive complexity of finite-state based grammars
  * automaton-based approaches to declarative constraint grammars, 
     constraints in optimality theory
  * parallel corpus annotations, register automata, acyclic timed automata

5. Machine learning of finite-state models of natural language

This topic includes but is not restricted to:

  * learning regular rule systems, learning topologies of finite automata and transducers
  * parameter estimation and smoothing, lexical openness
  * computer-driven grammar writing, user-driven grammar learning, discovery procedures
  * data scarcity, realistic variations of Gold's model, learnability and cognitive science
  * incompletely specified finite-state networks
  * model-theoretic grammars, gradient well/ill-formedness

6. Finite-state manipulation software (with relevance to the above themes)

This topic includes but is not restricted to

  * regular expression pre-compilers such as regexopt, xfst2fsa, standards and interfaces 
     for finite-state based software components, conversion tools
  * tools such as LEXC, Lextools, Intex, XFST, FSM, GRM, WFSC, FIRE Engine, FADD, FSA/UTR,
     SRILM, FIRE Station and Grail
  * free or almost free software such as MIT FST, Carmel, RWTH FSA, FSA Utilities, FSM<2.0>,
     Unitex, OpenFIRE, OpenFST, Vaucanson, SFST, PCKIMMO, MONA, Hopskip, ASTL, UCFSM,
     HaLeX, SML, and WFST (see http://forums.csc.fi/kitwiki/pilot/view/KitWiki/FsmReg for more
     examples)
  * results obtainable with such exploration tools as automata, Autographe, Amore, and TESTAS
  * visualization tools such as Graphviz and Vaucanson-G
  * language-specific resources and descriptions, freely available benchmarking resources

The descriptions of the topics above are not meant to be complete, and
should extend to cover all traditional FSMNLP topics. Submitted papers
or abstracts may fall in several categories.


SUBMISSION

We expect three kinds of submissions: 

- full papers, 
- short papers, and
- interactive software demos. 

Submissions are electronic and in PDF format via a web-based submission server. 
Authors are encouraged to use Springer LNCS style (Proceedings and Other Multiauthor Volumes)
for LaTeX in producing the PDF document. More information on this style can be found at:
http://www.springer.com/east/home/computer/lncs?SGWID=5-164-7-72376-0
The page limit for full papers is 12 pages, whereas short papers and 
software demo descriptions are limited to 6 pages. The information about the author(s) 
should be omitted in the submitted papers since the review process wil be blind. 
More detailed information about submission is available on: 
http://langtech.jrc.it/FSMNLP2008/m/submission.html


PUBLICATION

The papers and abstracts will be published in FSMNLP 2008 proceedings (paper version). 
We are currently negotiating publishing the postproceedings with a scientific press company.
Publication of extended and revised versions of the papers in a special journal issue 
is planned too. 


IMPORTANT DATES

Paper submissions due:  11 May 
Notification of acceptance:  11 June
Camera-ready versions due: 30 June 


PROGRAM COMMITTEE

Cyril Allauzen (Google Research, New York, USA) 
Francisco Casacuberta (Instituto Tecnologico De Informática, Valencia, Spain) 
Jean-Marc Champarnaud (Université de Rouen, France) 
Maxime Crochemore (Department of Computer Science, King's College London, U.K.) 
Jan Daciuk (Gdańsk University of Technology, Poland) 
Karin Haenelt (Fraunhofer Gesellschaft and University of Heidelberg, Germany) 
Thomas Hanneforth (University of Potsdam, Germany) 
Colin de la Higuera (Jean Monnet University, Saint-Etienne, France) 
André Kempe (Yahoo Search Technologies, Paris, France) 
Derrick Kourie (Dept. of Computer Science, University of Pretoria, South Africa) 
Andras Kornai (Budapest Institute of Technology, Hungary and MetaCarta, Cambridge, USA) 
Marcus Kracht (Univeristy of California, Los Angeles, USA) 
Hans-Ulrich Krieger (DFKI GmbH, Saarbrücken, Germany) 
Eric Laporte (Université de Marne-la-Vallée, France) 
Stoyan Mihov (Bulgarian Academy of Sciences, Sofia, Bulgaria) 
Herman Ney (RWTH Aachen University, Germany) 
Kemal Oflazer (Sabanci University, Turkey and Carnegie Mellon University, Pittsburgh, USA) 
Jakub Piskorski (Joint Research Center of the European Commission, Italy) 
Michael Riley (Google Research, New York, USA) 
Strahil Ristov (Ruder Boskovic Institute, Zagreb, Croatia) 
Wojciech Rytter (Warsaw University, Poland) 
Jacques Sakarovitch (Ecole nationale supérieure des Télécommunications, Paris, France) 
Max Silberztein (Université de Franche-Comté, France) 
Wojciech Skut (Google Research, Mountain View, USA) 
Bruce Watson (Dept. of Computer Science, University of Pretoria, South Africa) 
Shuly Wintner (University of Haifa, Israel) 
Atro Voutilainen (Connexor Oy, Finland) 
Anssi Yli Jyrä (University of Helsinki and CSC – Scientific Computing Ltd., Espoo, Finland) 
Sheng Yu (University of Western Ontario, Canada) 
Lynette van Zijl (Stellenbosch University, South Africa)

Received on Saturday, 15 March 2008 20:35:04 UTC