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

alexis nasr alexis.nasr at
Fri May 4 15:24:02 UTC 2001

                     Call for Papers

             for a Special Issue of the Journal

                Natural Language Engineering


     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

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
          Multimedia Document Analysis
          Robust Parsing
          Incremental Parsing
          Discourse analysis
          Complexity of linguistic analysis
          Hybrid methods in computational linguistics
          Text Mining
          Corpus linguistics
          Indexing and Information Retrieval


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: In case of
difficulty there is a helpline available on e-mail:
texline at 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.


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


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


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.


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 any information related to the organization, please contact:

Vincenzo Pallotta

IN F Ecublens
1015 Lausanne

tel. +41-21-693 52 97
fax. +41-21-693 52 78
Vincenzo.Pallotta at
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