Corpora: CFP: NLE journal special issue on Robust Methods in Analysis of Natural Language Data

From: Vincenzo Pallotta (Vincenzo.Pallotta@epfl.ch)
Date: Mon Apr 30 2001 - 17:42:27 MET DST

  • Next message: Stefan.Wermter: "Corpora: PG Research Student Applications"

                         Call for Papers

                 for a Special Issue of the Journal

                    Natural Language Engineering

                                on

         Robust Methods in Analysis of Natural Language Data

                     Special Issue guest editors:

                             Afzal Ballim
                          Vincenzo Pallotta

                    Department of Computer Science
          Swiss Federal Institute of Technology - Lausanne.

    The automated analysis of natural language data has become a central
    issue in the design of Intelligent Information Systems. The term
    "natural language" is intended to cover all the possible modalities of
    human communication and it is not restricted to written or spoken
    language. Processing unrestricted natural language is still
    considered as an AI-hard task. However various analysis techniques
    have been proposed in order to address specific aspects of natural
    language. In particular, recent interest has been on providing
    approximate analysis techniques, assuming that perfect analysis is not
    possible, but that partial results are still very useful.

    There are many ways in which the topic of robustness may be tackled:
    as a competency problem, as a problem of achieving interesting partial
    results, as a shallow analysis method, etc. What they have in common
    is that no simple combination of "complete" analysis modules for
    different linguistic levels in a chain can give a robust system,
    because they cannot adequately account for real-world data. Rather,
    robustness must be considered as a system-wide concern. We consider of
    central interest improving and integrating various processing methods
    with respect to the following issues:

    * Extending coverage

    * Improving efficiency

    * Disambiguation ability

    * Approximate processing

    * Enhancement of underlying theories

    Robustness may be seen as an engineering "add-on" - something that we
    add to a system to take account of the inability of our theories to
    cope with real-world data - or as a basic element of our theories -
    our theories are developed to admit that understanding of the domain
    can be incomplete. Both approaches may be valid under certain
    circumstances.

    The main goal of this Special Issue of the Natural Language
    Engineering journal is devoted to advances in fields like artificial
    intelligence, computational linguistics, human-computer interaction,
    cognitive sciences who are faced with the problem of feasible and
    reliable NLP systems implementation. Theoretical aspects of robustness
    in NLP are welcome as well as engineering and industrial experiences.

    We invite papers on all topics related to Robustness in Natural
    Language Processing and Understanding, including, but not limited to:

              Text Analysis
              Knowledge and Information Extraction
              Spoken Dialogue Systems
              Multimodal Human-Computer interfaces
              Natural Language Architectures
              Distributed NLP
              NLP and Soft Computing
              Semantics
              Underspecification
              Multimedia Document Analysis
              Robust Parsing
              Incremental Parsing
              Discourse analysis
              Summarization
              Complexity of linguistic analysis
              Hybrid methods in computational linguistics
              Text Mining
              Corpus linguistics
              Indexing and Information Retrieval

    SUBMISSION PROCEDURE:

    We are expecting full papers to describe original, previously
    unpublished research, be written in English, and not be simultaneously
    submitted for publication elsewhere (previous publication of partial
    results at workshops with informal proceedings is allowed).

    Papers should be formatted according to the NLE journal instructions
    and should be between 15 and 25 pages long. The preferred formatting
    system is LaTex, which can be used for direct typesetting, and a style
    file is available through anonymous ftp from the following address:
    ftp.cup.cam.ac.uk/pub/texarchive/journals/latex/nle-sty/. In case of
    difficulty there is a helpline available on e-mail:
    texline@cup.cam.ac.uk. If LaTex is not available, the publisher may be
    able to use alternative formatting systems (please specify which was
    used (e.g. WordPerfect 5.0, MSWord2000,etc.)), but reserves the right
    in all cases to typeset any paper by conventional means.

    IMPORTANT DATES:

    Papers due: 30 June 2001
    Acceptance notice: 30 October 2001
    Final version due: 31 January 2002
    Journal publication: (after March 2002)

    REVIEWING COMMITTEE:

    Jerry Hobs
    Massimo Poesio
    Karsten Worm
    Fabio Ciravegna
    John Carroll
    Ted Briscoe
    Michael Hess
    Kay-Uwe Carstensen
    Susan Armstrong
    Yorik Wilks
    Dan Cristea
    Liviu Ciortuz
    Eric Wherli
    Fabio Rinaldi
    Rodolfo Delmonte
    Wolfgang Menzel
    Salah Ait-Mokhtar
    Alberto Lavelli
    Rens Bod
    Joachim Niehren
    Roberto Basili
    Maria Teresa Pazienza
    Manuela Boros
    Diego Mollá-Aliod
    Hervé Bourlard
    B. Srinivas
    C.J. Rupp
    Peter Asveld
    Hatem Ghorbel
    Giovanni Coray
    Martin Rajman
    Jean-Cédric Chappelier

    ABOUT THE JOURNAL

    Natural Language Engineering is an international journal designed to
    meet the needs of professionals and researchers working in all areas
    of computerised language processing, whether from the perspective of
    theoretical or descriptive linguistics, lexicology, computer science
    or engineering. Its principal aim is to bridge the gap between
    traditional computational linguistics research and the implementation
    of practical applications with potential real-world use. As well as
    publishing research articles on a broad range of topicsfrom text
    analysis, machine translation and speech generation and synthesis to
    integrated systems and multi modal interfaces the journal also
    publishes book reviews. Its aim is to provide the essential link
    between industry and the academic community.

    Natural Language Engineering encourages papers reporting research with
    a clear potential for practical application. Theoretical papers that
    consider techniques in sufficient detail to provide for practical
    implementation are also welcomed, as are shorter reports of on-going
    research, conference reports, comparative discussions of NLE products,
    and policy-oriented papers examining e.g. funding programmes or market
    opportunities. All contributions are peer reviewed and the review
    process is specifically designed to be fast, contributing to the rapid
    publication of accepted papers.

    Editors

    B. K. Boguraev
    IBM Thomas J. Watson Research Center, New York, USA

    Christian Jaquemin
    University of Paris (LIMSI), FR

    John I. Tait
    University of Sunderland, UK

    FOR MORE INFORMATION:

    http://lithwww.epfl.ch/romand2000/nle.html

    For any information related to the organization, please contact:

    Vincenzo Pallotta

    DI-LITH EPFL
    IN F Ecublens
    1015 Lausanne
    Switzerland

    tel. +41-21-693 52 97
    fax. +41-21-693 52 78
    Vincenzo.Pallotta@epfl.ch



    This archive was generated by hypermail 2b29 : Wed May 02 2001 - 09:11:53 MET DST