Learning for natural language: final updated call

[Stefan Wermter]

                       CALL FOR PAPERS AND PARTICIPATION


                            IJCAI-95 Workshop on


         New Approaches to Learning for Natural Language Processing


       International Joint Conference on Artificial Intelligence (IJCAI-95)
                      Palais de Congres,  Montreal, Canada

                               August 21, 1995




ORGANIZING COMMITTEE
--------------------

Stefan Wermter          Gabriele Scheler              Ellen Riloff
University of Hamburg   Technical University Munich   University of Utah


INVITED SPEAKERS
----------------
Eugene Charniak, Brown University, USA
Noel Sharkey, Sheffield University, UK


PROGRAM COMMITTEE
-----------------

Jaime Carbonell, Carnegie Mellon University, USA
Joachim Diederich, Queensland University of Technology, Australia
Georg Dorffner, University of Vienna, Austria
Jerry Feldman, ICSI, Berkeley, USA
Walther von Hahn, University of Hamburg, Germany
Aravind Joshi, University of Pennsylvania, USA
Ellen Riloff, University of Utah, USA
Gabriele Scheler, Technical University Munich, Germany
Stefan Wermter, University of Hamburg, Germany


WORKSHOP DESCRIPTION
--------------------

In the last few years, there has been a great deal of interest and activity  in
developing  new approaches to learning for natural language processing. Various
learning methods have been used, including

- connectionist methods/neural networks
- machine learning algorithms
- hybrid symbolic and subsymbolic methods
- statistical techniques
- corpus-based approaches.

In general, learning methods are designed to support automated knowledge
acquisition, fault tolerance, plausible induction, and rule inferences. Using
learning methods for natural language processing is especially important
because language learning is an enabling technology for many other language
processing problems, including  noisy speech/language integration, machine
translation, and information retrieval. Different methods support language
learning to various degrees but, in general, learning is important for building
more flexible, scalable, adaptable, and portable natural language systems.

This workshop is of interest particularly at this time because systems built by
learning methods have reached a level where they can be applied to real-world
problems in natural language processing and where they can be compared with
more traditional encoding methods. The workshop will bring together researchers
from the US/Canada, Europe, Japan, Australia and other countries working on new
approaches to language learning.

The workshop will provide a forum for discussing various learning approaches
for supporting natural language processsing. In particular the workshop will
focus on questions like:

- How can we apply suitable existing learning methods for language processing?

- What new learning methods are needed for language processing and why?

- What language knowledge should be learned and why?

- What are similarities and differences between different approaches for
  language learning? (e.g., machine learning algorithms vs neural networks)

- What are strengths and limitations of learning rather than manual encoding?

- How can learning and encoding be combined in symbolic/connectionist systems?

- Which aspects of system architectures and knowledge engineering have to
  be considered? (e.g., modular, integrated, hybrid systems)

- What are successful applications of learning methods in various fields?
  (speech/language integration, machine translation, information retrieval)

- How can we evaluate learning methods using real-world language?
  (text, speech, dialogs, etc.)


WORKSHOP FORMAT
---------------

The workshop will provide a forum for the interactive exchange of ideas and
knowledge. Approximately 30-40 participants are expected and there will be time
for up to 15 presentations depending on the number and quality of paper
contributions received. Normal presentation length will be 15+5 minutes,
leaving time for direct questions after each talk. There may be a few invited
talks of 25+5 minutes length.  In addition to prepared talks, there will be
time for moderated discussions after two related sessions. Furthermore, the
moderated discussions will provide an opportunity for an open exchange of
comments, questions, reactions, and opinions.

PUBLICATION
-----------

Workshop proceedings will be published by AAAI.  If there is sufficient
interest of the participants of the workshop there may be a possibility to
publish the results of the workshop as a book.

REGISTRATION
------------

This workshop will take place directly before the general IJCAI-conference. It
is an IJCAI policy, that workshop participation is not possible without
registration for the general conference.

SUBMISSIONS
-----------

All submissions will be refereed by the program committee and other experts in
the field. Please submit 4 hardcopies AND a postscript file. The paper format
is the IJCAI95 format:  12pt article style latex, no more than 43 lines, 15
pages maximum, including title, address and email address, abstract, figures,
references. Papers should fit to 8 1/2" x 11" size. Notifications will be sent
by email to the first author.

Postscript files can be uploaded with anonymous ftp:

ftp nats4.informatik.uni-hamburg.de (134.100.10.104)
login: anonymous
password: <your email address>
cd incoming/ijcai95-workshop
binary
put <yourlastname.Z or yourlastname.gz>
quit

Hardcopies AND postscript files  must arrive not later than 24th February 1995
at the address below.

##############Submission Deadline:  24th February 1995
##############Notification Date: 24th March 1995
##############Camera ready Copy: 13th April 1995



Please send correspondence and submissions to:


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Dr. Stefan Wermter
Department of Computer Science
University of Hamburg
Vogt-Koelln-Strasse 30
D-22527 Hamburg
Germany

phone:  +49 40 54715-531
fax:    +49 40 54715-515
e-mail: wermter at informatik.uni-hamburg.de
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