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2nd Call for Papers: ICDM 05 Workshop on Knowledge Acquisition from Distributed, Semantically Heterogeneous Data and Knowledge Sources

From: Vasant Honavar <honavar@cs.iastate.edu>
Date: Fri, 12 Aug 2005 18:03:14 -0500
Message-ID: <42FD2AB2.8040009@cs.iastate.edu>
To: agents@cs.umbc.edu, dai-list@mcc.com, ontology@listserv.ieee.org, public-semweb-lifesci@w3.org, kaw@science.uva.nl, ml@isle.org, DISTRIBUTED-AI@JISCMAIL.AC.UK, protege-owl@smi.stanford.edu

(Apologies in advance if you receive multiple copies)**

IEEE Workshop on* *Knowledge Acquisition from Distributed, Autonomous, 
Semantically Heterogeneous Data and Knowledge Sources 
*(http://www.cild.iastate.edu/events/ICDM2005Workshop.html), New 
Orleans, Louisiana, USA, November 27, 2005

Organized in conjunction with *The Fifth IEEE International Conference 
on Data Mining*, New Orleans, Louisiana, USA, 2005

*Workshop Goals

*The workshop aims to bring together researchers in relevant areas of 
artificial intelligence (machine learning, data mining, knowledge 
representation, ontologies), information systems (information 
integration, databases, semantic Web), distributed computing, and 
selected application areas (e.g., bioinformatics, security informatics, 
environmental informatics) to address several questions that arise in 
the process of knowledge acquisition from distributed, autonomous, 
semantically heterogeneous data and knowledge sources.

*Topics of Interest

*Topics of interest include, but are not restricted to:
..    Challenges presented by emerging data-rich application domains such 
as bioinformatics, health informatics, security informatics, social 
informatics, environmental informatics.
..    Knowledge discovery from distributed data (assuming different types 
of data fragmentation, e.g., horizontal or vertical data fragmentation; 
different hypothesis classes, e.g., na´ve Bayes, decision tree; 
different performance criteria, e.g., accuracy versus complexity versus 
reliability of the model generated, etc.).
..    Making semantically heterogeneous data sources self-describing 
(e.g., by explicitly associating ontologies with data sources and 
mappings between them) in order to help collaborative science .
..    Representation, manipulation, and reasoning with ontologies and 
mappings between ontologies.
..    Learning ontologies from data (e.g., attribute value taxonomies).
..    Learning mappings between semantically heterogeneous data source 
schemas and between their associated ontologies.
..    Knowledge discovery in the presence of ontologies (e.g., attribute 
value taxonomies) and partially specified data (data described at 
different levels of abstraction within an ontology)?
..    Online query relaxation when an initial query posed to the data 
sources fails (i.e., returns no tuples), or equivalently, query-driven 
mining of the individual sources that will result in knowledge that can 
be used for query relaxation.

*Submission Instructions

*Postscript or PDF versions of papers, no more than 10 pages long 
(including figures, tables, and references) in the ICDM camera-ready 
format (IEEE 2-column format), should be submitted electronically to 
kadash-icdm05@cs.iastate.edu by  September 7, 2005. Each paper will be 
rigorously refereed by at least 2 reviewers for technical soundness, 
originality, and clarity of presentation. Accepted papers will be 
included in informal workshop proceedings published by ICDM and 
distributed at the workshop. Additional details about the workshop will 
be available at:


*Important Dates

*September 7: Paper Due                     
Oct. 1: Notification
Oct. 15: Camera Ready Due
Nov. 27: Workshop

*Organizing Committee

*Doina Caragea,  dcaragea@cs.iastate.edu
Iowa State University

Vasant Honavar, honavar@cs.iastate.edu
Iowa State University

Ion Muslea, imuslea@languageweaver.com
Language Weaver, Inc.

Raghu Ramakrishnan, raghu@cs.wisc.edu
University of Wisconsin-Madison

*Program Committee

*Naoki Abe, IBM
Liviu Badea, ICI, Romania
Doina Caragea, Iowa State Univ.
Marie desJardins, UMBC
C. Lee Giles, Penn State Univ.
Vasant Honavar, Iowa State Univ.
Hillol Kargupta, UMBC
Sally McClean, U. of Ulster, UK
Bamshad Mobasher - DePaul U.
Ion Muslea, Language Weaver, Inc.
C. David Page, Univ. of Wisconsin
Alexandrin Popescul - Ask Jeeves
Raghu Ramakrishnan, Univ. of Wisconsin
Steffen Staab - Univ. of Koblenz


Dr. Vasant Honavar
Artificial Intelligence Research Laboratory
Department of Computer Science
211 Atanasoff Hall
Iowa State University
Ames, IA 50011-1040

email: honavar@cs.iastate.edu
voice: 515 294 1098
fax:   515 294 0258
www:   http://www.cs.iastate.edu/~honavar/

Professor and Director of Research, Computer Science
Professor, Bioinformatics and Computational Biology 
Professor and Director, Center for Computational Intelligence, Learning, and Discovery 
Professor, Neuroscience
Professor, Human Computer Interaction
Professor, Information Assurance
Member, Laurence H. Baker Center for Bioinformatics and Biological Statistics
Member, Information Assurance Center
Co Editor in Chief,  Cognitive Systems Research
Editor, Machine Learning Journal 
Received on Sunday, 14 August 2005 03:39:29 UTC

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