- From: Paul Buitelaar <paulb@dfki.de>
- Date: Thu, 01 Apr 2004 17:33:55 +0200
- To: www-rdf-interest@w3.org, www-annotation@w3.org, news-announce-conferences@uunet.uu.net, kaw@swi.psy.uva.nl, acl@opus.cs.columbia.edu, community@mlnet.org, ontoweb-language-sig@cs.man.ac.uk, daml-all@daml.org, ontoweb-list@www1-c703.uibk.ac.at, seweb-list@www1-c703.uibk.ac.at, irlist-editor@acm.org, semanticweb@yahoogroups.com, corpora@hd.uib.no
- Cc: Siegfried Handschuh <sha@aifb.uni-karlsruhe.de>, Bernardo Magnini <magnini@itc.it>
(With apologies for multiple postings.) ** Deadline: April 15th ** Call for Papers ECAI-2004 Workshop on Ontology Learning and Population: Towards Evaluation of Text-based Methods in the Semantic Web and Knowledge Discovery Life Cycle 16th European Conference on Artificial Intelligence August 22nd/23rd 2004 Valencia, Spain http://olp.dfki.de/ecai04/cfp.htm With Support From: KnowledgeWeb (http://knowledgeweb.semanticweb.org/) Topic and Motivation ---------------- Ontologies are formal, explicit specifications of shared conceptualizations, representing concepts and their relations that are relevant for a given domain of discourse. Currently, ontologies are mostly developed (including ontology construction, extension, mapping and merging) as well as used (ontology population through knowledge markup) by a manual process, which is very ineffective and may cause major barriers to their large-scale use in such areas as Knowledge Discovery and Semantic Web. The expected central role of ontologies in the organization and functioning of the Semantic Web has been well documented in recent years. Somewhat less traditional is the role of ontologies in incremental approaches to Knowledge Discovery, in which ontologies and machine learning methods are used in combination to mine, interpret and (re-)organize knowledge. As human language is a primary mode of knowledge transfer, linguistic analysis of relevant documents for ontology learning and population seems a viable option. More precisely, automation of these tasks can be implemented by a combined use of linguistic analysis and machine learning approaches for text mining. The workshop will therefore be concerned with reports on the development of such methods, but specifically also with the quantitative evaluation of these methods. Automatic methods for text-based ontology learning and population have developed over recent years (e.g. results from the ECAI-2000, IJCAI-2001, ECAI-2002 workshops on Ontology Learning and the KCAP-2001, ECAI-2002, KCAP-2003 workshops on Knowledge Markup / Ontology Population), but a remaining challenge is to evaluate in a quantitative manner how useful or accurate the extracted ontology classes, properties and instances are. In fact, this is a central issue as it is currently very hard to compare methods and approaches, due to the lack of a shared understanding of the task at hand. The core theme of the workshop therefore will be to develop such a shared understanding through the definition of a clear task (and corresponding sub-tasks), identify resources needed for the task/sub-tasks and to discuss how best to develop an open source evaluation platform. Areas of Interest ------------ Submissions are invited on these topics in Ontology Learning and Population (OLP): * Evaluation Methodologies and Metrics for OLP - Including Experience and Best Practice from Related Evaluation Efforts in the Context of CLEF, TREC, SENSEVAL, etc. * Datasets and Resources for the Evaluation of OLP * Definition of Sub-Tasks for OLP - Extraction of Taxonomy, Class-hierarchy - Extraction of Class-properties, Relations - Extraction of Class-instances, Individuals * Definition of Related Tasks - Ontology Extension, Evolution - Ontology Mapping - Ontology Merging * Text-based Approaches for OLP, for instance (Combinations of): - NLP and Linguistic Analysis for OLP - (NLP-based) Text-mining for OLP - (Ontology-aware) Information Extraction for OLP * OLP in the Context of the Semantic Web * OLP in the Context of Knowledge Discovery Workshop Schedule --------------- This will be a one-day workshop with a proposed schedule of 2 or 3 paper sessions and a poster session. The workshop will include a round-table working session on the topic of evaluation of ontology learning and population. It is expected that the outcome of this discussion will lead to a written report on guidelines for setting up an evaluation platform for these tasks. Organizing Committee ----------------- Paul Buitelaar (DFKI) paulb@dfki.de Siegfried Handschuh (AIFB) sha@aifb.uni-karlsruhe.de Bernardo Magnini (IRST) magnini@itc.it Program Committee --------------- AIFB - Siegfried Handschuh, Steffen Staab, York Sure Bar Ilan University - Ido Dagan DFKI - Paul Buitelaar, Andreas Eisele, Michael Sintek IRIT, Toulouse - Nathalie Aussenac-Gilles IRST - Bernardo Magnini Josef Stefan Inst. - Marko Grobelnik KDLabs - Jörg-Uwe Kietz LOA-CNR - Aldo Gangemi MIG-INRA - Claire Nedellec NCSR Demokritos - Georgios Paliouras NLM-NIH - Vipul Kashyap Univ. Antwerpen - Walter Daelemans Univ. Basque Country - Eneko Agirre Univ. Paris 13, LIPN - Adeline Nazarenko Univ. Poly. Madrid - Asuncion Gomez-Perez Univ. Roma La Sapienza - Paola Velardi Univ. Roma Tor Vergata - Roberto Basili Univ. Saarland - Thierry Declerck Univ. Sheffield - Fabio Ciravegna, Hamish Cunningham, Yorick Wilks USC/ISI - Eduard Hovy XRCE - Eric Gaussier Submissions --------- Submissions (in PS or PDF format) should be in English and no longer than 6 pages, following the formatting style for ECAI-2004. Submissions should be sent by email to the contact person: paulb@dfki.de April 15th - Paper submission deadline May 15th - Notification of acceptance/rejection June 15th - Camera-ready papers August 22nd/23rd - Workshop Workshop Attendance and Registration ----------------------------- All workshop participants must register for ECAI-2004
Received on Thursday, 1 April 2004 10:37:59 UTC