FINAL 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@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@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@cs.utexas.edu
General Inquiries:
Please address general inquiries to:
Up-to-date information will be maintained on the WWW at:
http://www.cs.utexas.edu/users/ml/mlj-nll
Co-Editors:
Raymond J. Mooney, University of Texas at Austin mooney@cs.utexas.edu
Claire Cardie, Cornell University cardie@cs.cornell.edu