IEEE Workshop on
Knowledge Acquisition from Distributed, Autonomous, Semantically Heterogeneous Data and Knowledge Sources

 

 

Houston, Texas, November 27, 2005
In conjunction with

ICDM'05: The Fifth IEEE International Conference on Data Mining 2005

                  
                  


 

Invited Talk:  "Scientific Data Integration: From the Big Picture to some Gory Details"

                                  by Dr. Bertram Ludaescher         

          List of Accepted Papers

          Tentative Workshop Schedule

          Invited Talk Slides
          Online Workshop Proceedings

 


 

Background:

Recent advances in high performance computing, high speed and high bandwidth communication, massive storage, and software (e.g., web services) that can be remotely invoked on the Internet present unprecedented opportunities in data-driven knowledge acquisition in a broad range of applications in virtually all areas of human endeavor including collaborative cross-disciplinary discovery in e-science, bioinformatics, e-government, environmental informatics, health informatics, security informatics, e-business, education, social informatics, among others. Given the explosive growth in the number and diversity of potentially useful information sources in many domains, there is an urgent need for sound approaches to integrative and collaborative analysis and interpretation of distributed, autonomous (and hence, inevitably semantically heterogeneous) data sources.

Machine learning offers some of the most cost-effective approaches to automated or semi-automated knowledge acquisition (discovery of features, correlations, and other complex relationships and hypotheses that describe potentially interesting regularities from large data sets) in many data rich application domains. However, the applicability of current approaches to machine learning in emerging data rich application domains presents several challenges in practice:



Topics of Interest:

The  workshop seeks 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 (service-oriented computing) and selected application areas (e.g., bioinformatics, security informatics, environmental informatics) to address several questions such as:


Submission Requirements:

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  October 9, 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.

Important Dates:

Paper submission

October 9, 2005

Notification of acceptance

October 16, 2005

Camera ready papers

October 22, 2005

Workshop date

November 27, 2005

Organizers:

Program Committee: