9.877, Calls: Interlinguas'98,ICGS'98
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LINGUIST List: Vol-9-877. Sat Jun 13 1998. ISSN: 1068-4875.
Subject: 9.877, Calls: Interlinguas'98,ICGS'98
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==========================================================================
Please do not use abbreviations or acronyms for your conference unless
you explain them in your text. Many people outside your area of
specialization will not recognize them. Also, if you are posting a
second call for the same event, please keep the message short. Thank
you for your cooperation.
=================================Directory=================================
1)
Date: Thu, 11 Jun 98 18:20:23 EDT
From: Priscilla Rasmussen <rasmusse at cs.rutgers.edu>
Subject: 2nd Workshop on Interlinguas CFP
2)
Date: Thu, 11 Jun 98 18:24:23 EDT
From: Priscilla Rasmussen <rasmusse at cs.rutgers.edu>
Subject: ICGI-98 Call for Papers
-------------------------------- Message 1 -------------------------------
Date: Thu, 11 Jun 98 18:20:23 EDT
From: Priscilla Rasmussen <rasmusse at cs.rutgers.edu>
Subject: 2nd Workshop on Interlinguas CFP
SECOND WORKSHOP ON INTERLINGUAS: CALL FOR PAPERS
FROM TEXT TO REPRESENTATION: SECOND WORKSHOP ON INTERLINGUAS
Tuesday, October 27, 1998 (preceding the AMTA 98 conference)
Sheraton Bucks County Hotel, Langhorne, Pennsylvania
[http://crl.nmsu.edu/Events/FWOI/SecondWorkshop/index.html]
The focus of this workshop will be a multi-lingual text and the task
of representing aspects of that text using an Interlingual
Representation (IL). The format is meant to encourage concrete
discussion on how ILs handle particular challenges, including, but not
limited to, representation of:
basic predicate/argument structure
noun phrases/referents
proper nouns
prepositional meaning
non-literal language
temporal relations
textual organization
lexical divergences
syntactic divergences
Submitters are invited to select some aspect or section of the text,
in a single language, or a language pair/set, and submit a short
position paper, describing the IL representation for that aspect.
In addition to providing concrete IL representations and terms
(ontological entities/atoms), submitters are encouraged to focus also
on the reasons why one would choose to define these particular terms,
and the justification for defining in a particular way the relations,
slots, and fillers of the term.
Papers should define the aspect to be discussed, identify instances in
the text, provide a representation for these instances, and categorize
the instances according to the treatment proposed. The papers will be
collected and published as the proceedings of the workshop.
Submission of end-to-end output of an IL system (including and
identifying relevant hand-crafted elements) is especially encouraged.
Submissions could also propose theoretical justification for a
particular framework, in particular how the building blocks of the
system work in handling an aspect of the text.
The workshop itself will consist of panels organized around the
representational aspects selected by the participants. The panel
presentations will be supplemented by periods for general discussion
and other activities.
Ideally, the result of the workshop will be
- in some cases, a consistent set of IL expressions for the various
problematic issues raised by the text and
- in other cases, a clearer delineation of
(1) how the various problematic issues in the text are treated in
different ILs and
(2) the fundamental differences in approach that motivate these
different IL treatments.
A final product of the workshop will be an outline of the issues
discussed in determining whether combined IL approaches are possible
and/or desirable. These results will provide a basis for further
workshops.
The multi-lingual text will be available at
http://crl.nmsu.edu/Events/FWOI/SecondWorkshop/text.html in glossed
English, French, Spanish, Chinese, Arabic, German, Russian, Persian,
Italian, Catalan, Vietnamese, Malay, Greek, Bulgarian, Tamil, and
Portuguese versions, as they become available.
Notice of interest in participation: July 10, 1998
(to shelmrei at crl.nmsu.edu)
(Please identify specifically what aspect of IL representation
you intend to address)
Position paper submission: August 10, 1998
Notifications: September 10, 1998
Final copies of papers: October 10, 1998
Workshop: October 27, 1998
Submission may be in printed or electronic form (LaTex, FrameMaker),
but should follow ACL style sheet (available at
http://www.cs.columbia.edu/~acl/home.html).
Submissions should be sent to:
Stephen Helmreich
Computing Research Laboratory
New Mexico State University
PO Box 30001/3CRL
Las Cruces, NM 88003 (USA)
phone: (505) 646-2141
fax: (505) 646-6218
e-mail: shelmrei at crl.nmsu.edu
The registration fee for the conference is $50. Non-presenters will
be accepted on a first-come, first served basis.
A copy of the registration form is available at:
http://crl.nmsu.edu/Events/FWOI/SecondWorkshop/registration.html
-------------------------------- Message 2 -------------------------------
Date: Thu, 11 Jun 98 18:24:23 EDT
From: Priscilla Rasmussen <rasmusse at cs.rutgers.edu>
Subject: ICGI-98 Call for Papers
Call For Participation
Fourth International Colloquium on Grammatical Inference (ICGI-98)
http://www.cs.iastate.edu/~icgi98/icgi98.html
Program Co-Chairs: Vasant Honavar and Giora Slutzki, Iowa State
University
July 12-14, 1998
Iowa State University
Ames, Iowa, USA.
- ----------------------------------------------------------------------
Cosponsored at Iowa State University by
International Institute of Theoretical and Applied Physics
Complex Adaptive Systems Group
Iowa Computational Biology Laboratory
Artificial Intelligence Research Laboratory
Department of Computer Science
In cooperation with
American Association for Artificial Intelligence
IEEE Systems, Man, and Cybernetics Society
ACL Special Interest Group on Natural Language Learning
------------------------------------------------------------------------
Introduction
Grammatical Inference, variously refered to as automata induction,
grammar induction, and automatic language acquisition, refers to the
process of learning of grammars and languages from data. Machine
learning of grammars finds a variety of applications in syntactic
pattern recognition, adaptive intelligent agents, diagnosis,
computational biology, systems modelling, prediction, natural language
acquisition, data mining and knowledge discovery.
Traditionally, grammatical inference has been studied by researchers
in several research communities including: Information Theory, Formal
Languages, Automata Theory, Language Acquisition, Computational
Linguistics, Machine Learning, Pattern Recognition, Computational
Learning Theory, Neural Networks, etc.
Perhaps one of the first attempts to bring together researchers
working on grammatical inference for an interdisciplinary exchange of
research results took place under the aegis of the First Colloquium on
Grammatical Inference held at the University of Essex in United
Kingdom in April 1993. This was followed by the (second) International
Colloquium on Grammatical Inference, held at Alicante in Spain, the
proceedings of which were published by Springer-Verlag as volume 862
of the Lectures Notes in Artificial Intelligence, and the Third
International Colloquium on Grammatical Inference, held at Montpellier
in France, the proceedings of which were published by Springer-Verlag
as volume 1147 of the Lecture Notes in Artificial
Intelligence. Following the success of these events and the Workshop
on Automata Induction, Grammatical Inference, and Language
Acquisition, held in conjunction with the International Conference on
Machine Learning at Nashville in United States in July 1997, the
Fourth International Colloquium on Grammatical Inference will be held
from July 12 through July 14, 1998, at Iowa State University in United
States.
- ----------------------------------------------------------------
Topics of Interest
The conference seeks to provide a forum for presentation and
discussion of original research papers on all aspects of grammatical
inference including, but not limited to:
* Different models of grammar induction: e.g., learning from examples,
learning using examples and queries, incremental versus
non-incremental learning, distribution-free models of learning,
learning under various distributional assumptions (e.g., simple
distributions), impossibility results, complexity results,
characterizations of representational and search biases of grammar
induction algorithms.
* Algorithms for induction of different classes of languages and
automata: e.g., regular, context-free, and context-sensitive
languages, interesting subsets of the above under additional syntactic
constraints, tree and graph grammars, picture grammars,
multi-dimensional grammars, attributed grammars, parameterized models,
etc.
* Theoretical and experimental analysis of different approaches to
grammar induction including artificial neural networks, statistical
methods, symbolic methods, information-theoretic approaches, minimum
description length, and complexity-theoretic approaches, heuristic
methods, etc.
* Broader perspectives on grammar induction -- e.g., acquisition of
grammar in conjunction with language semantics, semantic constraints
on grammars, language acquisition by situated agents and robots,
acquisition of language constructs that describe objects and events in
space and time, developmental and evolutionary constraints on language
acquisition, etc.
* Demonstrated or potential applications of grammar induction in
natural language acquisition, computational biology, structural
pattern recognition, information retrieval, text processing, adaptive
intelligent agents, systems modelling and control, and other domains.
- ------------------------------------------------------------------
Program Committee
Technical Program Chairs:
Vasant Honavar and Giora Slutzki, Iowa State University, USA.
Technical Program Committee:
R. Berwick, MIT, USA
A. Brazma, European Bioinformatics Institute, Cambridge, UK.
M. Brent, Johns Hopkins University, USA
C. Cardie, Cornell University, USA
W. Daelemans, Tilburg University, Netherlands
D. Dowe, Monash University, Australia
P. Dupont, University Jean Monnet at St. Etienne, France.
D. Estival, University of Melbourne, Australia
J. Feldman, International Computer Science Institute, Berkeley, USA
L. Giles, NEC Research Institute, Princeton, USA
J. Gregor, University of Tennessee, USA
C. de la Higuera, University Jean Monnet at St. Etienne, France
A. Itai, Technion, Israel
T. Knuutila, University of Turku, Finland
J. Koza, Stanford University, USA
K. Lang, NEC Research Institute, Princeton, USA.
M. Li, University of Waterloo, Canada
E. Makinen, University of Tampere, Finland
L. Miclet, ENSSAT, Lannion, France.
G. Nagaraja, Indian Institute of Technology, Bombay, India
H. Ney, University of Technology, Aachen, Germany
J. Nicolas, IRISA, France
R. Parekh, Allstate Research and Planning Center, Menlo Park, USA
L. Pitt, University of Illinois at Urbana-Champaign, USA
D. Powers, Flinders University, Australia
L. Reeker, National Science Foundation, USA
Y. Sakakibara, Tokyo Denki University, Japan.
C. Samuelsson, Lucent Technologies, USA
A. Sharma, University of New South Wales, Australia.
E. Vidal, U. Politecnica de Valencia, Spain
- -------------------------------------------------------------------
Local Arrangements Committee
Dale Grosvenor, Iowa State University, USA.
K. Balakrishnan, Iowa State University, USA.
R. Bhatt, Iowa State University, USA
J. Yang, Iowa State University, USA.
------------------------------------------------------------------------
Invited Papers
1. J. Feldman, International Computer Science Institute and University
of California, Berkeley, CA, USA. Topic: Natural Language Acquisition
(Exact title to be announced).
2. A. Brazma, European Bioinformatics Institute, Cambridge. Topic:
Pattern Discovery in Biosequences. (Exact title to be announced).
- -----------------------------------------------------------------
Tutorial(s)
1. Kolmogorov Complexity and Its Applications, Jack Lutz, Iowa State
University.
- -------------------------------------------------------------------
List of Accepted Papers
1. Stochastic Regular Tree Language Inference, Rafael C. Carrasco, Jose
Oncina and Jorge Calera
2. The Data Driven Approach Applied to the OSTIA Algorithm, Jose Oncina
3. Approximate Learning of Random Subsequential Transducers, Antonio
Castellanos
4. How considering incompatible state mergings may reduce the DFA
induction search tree, Francois Coste and Jacques Nicolas
5. Learning Regular Grammars to Model Musical Style: Comparing
Different Coding Schemes, P. P. Cruz-Alcazar and E. Vidal-Ruiz
6. Using symbol clustering to improve probabilistic automaton
inference, Pierre Dupont and Lin Chase
7. Learning a Subclass of Context-Free Languages J. Emerald, K.
Subramanian, and D. Thomas
8. Learning a determinisitic finite automaton with a recurrent neural
network, L Firoiu, T Oates, and P R Cohen
9. Learning Feature-Based Phrase-Structure Rules with the Grammar
Inference Tool, B. Geistert
10. Learning Stochastic Finite Automata from Experts, Colin de la
Higuera.
11. A stochastic search approach to grammar induction Hugues Juille
and Jordan Pollack
12. Grammar Model and Grammar Induction in the System NL Page, Keselj
13. Results of the Abbadingo One DFA Learning Competition and a New
Evidence Driven State Merging Algorithm K.J. Lang, B.A. Pearlmutter
and R. Price
14. Transducer-learning Experiments on Language Understanding Pics and
E. Vidal
15. Learning k-variable pattern languages efficiently stochastically
finite on average from positive data Peter Rossmanith and Thomas
Zeugmann
16. Locally Threshold Testable Languages in Strict Sense: Application
to the Inference Problem, Jose Ruiz, Salvador Espana, and Pedro Garcia
17. Grammatical Inference in Document Recognition, Saidi, Tayeb-bey
18. Learning a Subclass of Linear Languages from Positive Structural
Information, Jose Sempere and G. Nagaraja
19. Why Meaning Helps Learning Syntax, Isabelle Tellier
20. A Performance Evaluation of automatic Survey Classifiers,
Viechnicki
21. Applying grammatical inference by learning a language model for
oral dialogue Jacques Chodorowski and Laurent Miclet
22. A polynomial Time incremental Algorithm for learning DFA,
R. Parekh, C. Nichitu, V. Honavar
- -------------------------------------------------------------------
Conference Format and Proceedings
The conference will include oral and possibly poster presentations of
accepted papers, a small number of tutorials and invited talks. All
accepted papers will appear in the conference proceedings to be
published by Springer-Verlag as a volume in the Lecture Notes in
Artificial Intelligence which is part of the Springer-Verlag Lecture
Notes in Computer Science Series.
Instructions for preparation of Camera-Ready Versions of Accepted and
Invited Papers for Publication
- ------------------------------------------------------------------
Financial Support
Limited financial support might be available, subject to the
availability of funds, for:
* scientists (especially junior researchers) from developing
countries, especially for those who can find other sources of support
for extended visit at a US institution
* graduate students and postdocs from US institutions
Additional details will be posted as they become available.
- ------------------------------------------------------------------
FOR ADDITIONAL DETAILS, SEE
http://www.cs.iastate.edu/~icgi98/icgi98.html
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