Machine Learning Journal Special Issue on Natural Language Learning

[Claire Cardie]

	                   CALL FOR PAPERS
 
                        Machine Learning Journal
                            Special Issue on
 
			Natural Language Learning
 

The application of learning techniques to natural language processing
has grown dramatically in recent years under the rubric of
"corpus-based," "statistical," or "empirical" methods.  However, most
of this research has been conducted outside the traditional machine
learning research community.  This special issue is an attempt to
bridge this divide by inviting researchers in all areas of natural
language learning to communicate their recent results to a general
machine learning audience.  Papers are invited on learning applied to
all natural language tasks including:

* Syntax: Part-of-Speech tagging, parsing, language modeling,
  prepositional-phrase attachment, spelling correction, word segmentation

* Semantics: Word-sense disambiguation, word clustering, lexicon acquisition,
  semantic analysis, database-query mapping

* Discourse: Information extraction, anaphora resolution, discourse
  segmentation

* Machine Translation: Bilingual text alignment, bilingual dictionary 
  construction, lexical, syntactic, and semantic transfer

and all learning approaches including:

* Statistical: n-gram models, hidden Markov models, probabilistic 
  context-free grammars, Bayesian networks

* Symbolic:  Decision trees, rule-based, case-based, inductive logic 
  programming, automata and grammar induction

* Neural-Network & Evolutionary: recurrent networks, self-organizing maps,
  genetic algorithms

Experimental papers with significant results evaluating either
engineering performance or cognitive-modeling validity on suitable
corpora are invited.  Papers will be evaluated by three reviewers,
including at least two experts in the relevant area of natural
language learning; however, they should be written to be reasonably
accessible to a general machine learning audience.
 
Schedule:

         December 1, 1997: Deadline for submissions
         March 1, 1998: Deadline for getting decisions back to authors
         May 1, 1998: Deadline for authors to submit final versions
         Fall 1998: Publication

Submission Guidelines:

 1) Manuscripts should conform to the formatting instructions in:

	 http://www.cs.orst.edu/~tgd/mlj/info-for-authors.html 

    The first author will be the primary contact unless otherwise stated.

 2) Authors should send 5 copies of the manuscript to:
 
         Karen Cullen
         Machine Learning Editorial Office
         Attn: Special Issue on Natural Language Learning
         Kluwer Academic Press
         101 Philip Drive
         Assinippi Park
         Norwell, MA 02061
         617-871-6300
         617-871-6528 (fax)
         kcullen at wkap.com
 
    and one copy to:
 
         Raymond J. Mooney
         Department of Computer Sciences
         Taylor Hall 2.124
         University of Texas
         Austin, TX 78712-1188
         (512) 471-9558
         (512) 471-8885 (fax)
         mooney at cs.utexas.edu

 3) Please also send an ASCII title page (title, authors, email, abstract, 
    and keywords) and a postscript version of the manuscript to 
    mooney at cs.utexas.edu.

 
 General Inquiries: 

   Please address general inquiries to: 

       mooney at cs.utexas.edu

   Up-to-date information will be maintained on the WWW at: 

       http://www.cs.utexas.edu/users/ml/mlj-nll


 Co-Editors:

   Claire Cardie       Cornell University               cardie at cs.cornell.edu 
   Raymond J. Mooney   University of Texas at Austin    mooney at cs.utexas.edu 
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