-----------------------------------------------------------------------
CALL FOR PAPERS
2nd LEARNING LANGUAGE IN LOGIC (LLL) WORKSHOP
13th - 14th September 2000, Lisbon - Portugal
Co-located with ICGI and CoNLL
http://www.lri.fr/~cn/LLL-2000
-----------------------------------------------------------------------
Presentation
------------
Our purpose is to provide a forum for discussion on all aspects of
learning linguistic knowledge in logic.
This workshop is a follow-up of the succesful LLL workshop held in
1999 in Bled, (Slovenia) and co-located with ICML
(http://www.cs.york.ac.uk/mlg/lll/workshop/).
It will be co-located with the International Conference on Grammar
Inference (ICGI) (http://vinci.inesc.pt/icgi-2000/) and the Conference
on Natural Language Learning (CoNLL)
(http://lcg-www.uia.ac.be/conll2000/cfp.html).
Aims and scope of the conference
--------------------------------
The fact that more and more people are interested in the automatic
acquisition of lexicons is due to the progress in the development of
applications in NLP, terminology acquisition, indexing, information
extraction, retrieval, question-answering, etc. Relational learning
seems like a valuable alternative to data analysis in some NLP
domains. This is clearly shown by the recent success of both NLP
methods based on ILP or non-classic logics, and hybrid methods.
Interest in learning linguistic knowledge has grown steadily over the
last 15 years. As compared to manual acquisition, specialized
resources can be learned, revised and extended with respect to the
task at hand for much less cost.
Despite the degree of variation in the applications and resources we
want to acquire, most of them are learned in the same way: by
observing regularities among the co-occurence of phenomena in the
corpus. Therefore, a large amount of work is naturally based on
statistics, and attempts to develop robust and large-scale methods.
Moreover, relational learning and logic-based learning have proved
their capacity to learn complex structured knowledge from structured
data and explicit background knowledge. Compared to data analysis,
some of the major advantages here are: a better means to express the
representation; a method that is easier to understand; and a
comprehensible learning result.
As a consequence, interest is growing for a corpus-based learning of
structures that represent linguistic resources such as
predicate-argument structures, grammars, ontologies, etc.
The goal of this workshop is to bring together researchers from many
subfields of AI who are working on learning from text, while
emphasizing the logic-based learning techniques and algorithms. These
techniques include,
* Instance-based and clustering approaches in relational learning
* Scalability issues (applying Logic-based methods to large data sets)
* Logical approaches to statistical NLP
* Theory revision
* Explanation-based learning
* Higher-order logic for LLL
* Handling very complex terms
* Multi-predicate learning
* Collaborative and interactive learning
* Learning in description logics
* Combinations of approaches and multi-strategy learning
* Evaluation techniques
* Information indexing, filtering, retrieval, extraction
* Text classification methods
* Question answering
* Learning ontologies, thesauri and lexicon
* Learning terminology
* Learning predicate-argument structure
* Shallow parsing
* Learning grammar
* Learning subcategorisation frames
* Part-of-speech tagging
* Morphosyntactic tagging
* Morphological analysis
In addition to these topics, the workshop covers all theoretical and
methodological issues concerning learning from text using logic- based
techniques. Submissions describing innovative applications are also
encouraged.
Important dates
---------------
Submission of papers by May, 15, 2000
Acceptance notices mailed by June, 19, 2000
Final, camera-ready papers due by July, 14, 2000
Organization
------------
The workshop will be two full days, including invited talks, paper
presentations, poster presentations, and numerous opportunities for
discussion. There will be joint sessions with the workshop
"International Conference on Grammar Inference" (ICGI) and the
"Conference on Natural Language Learning" (CoNLL) on topics of common
interest. Joint sessions will include invited talks and paper
presentations, depending on submissions.
Submission procedure
-------------------
Full papers may be up to 10 pages, short papers up to 6 pages, both
in a 11 point font and single-spaced. We accept either electronic
submission (preferred), in Postscript, PDF or Word format, or paper
submissions (in 4 copies) to the following address:
Claire Nedellec
LLL workshop
LRI, Bat 490 e-mail: cn@lri.fr
Universite Paris-Sud Tel: +33 (0)1 69 15 66 26
F-91405 Orsay Fax: +33 (0)1 69 15 65 86
FRANCE
Program committee
-----------------
Program chair
-------------
Claire Nedellec (LRI, University of Paris-Sud, France)
Members
-------
Pieter Adriaans (Syllogic and University of Amsterdam, Netherlands)
Roberto Basili (University of Roma, Italy)
Gilles Bisson (INRIA, Grenoble, France)
Henrik Boström (University of Stockholm, Sweden)
Gosse Bouma (University of Groningen, Netherlands)
James Cussens (University of York, UK)
Tomaz Erjavec (Institute Jozef Stefan, Slovenia)
Daniel Kayser (LIPN, University Paris-Nord, France)
Suresh Manandhar (University of York, UK)
Guenter Neumann (DFKI, Germany)
Steve Pulman (University of Cambridge, UK)
Christer Samuelsson (XRCE, Grenoble, France)
Stefan Wrobel (University of Magdeburg, Germany)
Organization
------------
Arlindo Oliveira (INESC, Lisbon, Portugal)
-------------------------------------------------------------------
Claire Nedellec
Inference and Machine Learning Group e-mail: cn@lri.fr
LRI, Bat 490 Tel: +33 (0)1 69 15 66 26
Universite Paris-Sud Fax: +33 (0)1 69 15 65 86
F-91405 Orsay
FRANCE
Web : http://www.lri.fr/~cn
-------------------------------------------------------------------
This archive was generated by hypermail 2b29 : Mon Mar 13 2000 - 09:55:50 MET