SPECIAL ISSUE ON DISTRIBUTED AND MOBILE DATA MINING
IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS, PART B
 

GUEST EDITORS:

Hillol Kargupta
University of Maryland Baltimore County
hillol@cs.umbc.edu

Sanghamitra Bandyopadhyay
Indian Statistical Institute
sanghami@isical.ac.in

Byung-Hoon Park
Oak Ridge National Laboratory
parkbh@ornl.gov
 

SCOPE:

Knowledge discovery and data mining deal with the problem of extracting interesting associations, classifiers, clusters, and other patterns from data. The emergence of network-based computing environments has introduced a new and important dimension to this problem, viz., that of distributed sources of data and computing. The Internet, corporate intranets, sensor networks, and even scientific computing domains (e.g., distributed active archive centers (DAAC) of the NASA Earth Observing System) support this observation. The advent of laptops, palmtops, handhelds, embedded systems, and wearable computers is also making ubiquitous access to a large quantity of distributed data a reality. Advanced analysis of distributed data for extracting useful knowledge is the next natural step in the increasingly connected world of ubiquitous and distributed computing.

Most of the popular data mining algorithms are designed to work for centralized data and they often do not pay attention to the resource constraints of distributed and mobile environments. Recent research in this area have demonstrated that handling these resource constraints in an optimal fashion requires a new breed of data mining algorithms and systems that are very different from their centralized counterparts. This special issue will focus on the state-of-the-art developments in the domain of distributed and mobile data mining. The topics of interest include, but are not limited to:

1. Theoretical foundations and algorithms: Advanced algorithms for mobile and distributed data mining applications.

2. Data management issues, mark-up languages, and other data representation techniques; integration with database applications for mobile environments.

3. Architectural issues: Architecture, control, security, and communication issues.

4. Data stream mining in distributed and mobile environments.

5. Resource and location aware mobile data mining tasks.

6. Experimental systems: Development of experimental systems, performance and design issues.

7. Applications of distributed and mobile data mining: in business, science, engineering, medicine, and other disciplines.

8. Human-computer interaction issues.

9. Web-based applications of distributed data mining and semantic web.

10. Privacy-preserving distributed and mobile data mining.
 
 
 

PAPER SUBMISSION INSTRUCTION:

Your paper must be submitted in Portable Document Format (pdf) or Postscript.  It must print correctly on 8.5 X 11 inch paper.  For Unix and Windows systems there are postscript to pdf converters, notably ps2pdf which is a part of ghostscript.  A text version of your abstract is required. When you are ready to submit, please follow this link to the SMC ManuscriptCentral site:  http://smcb-ieee.manuscriptcentral.com/

You will have to create an account, if you do not yet have one.  Then you will log in and be asked for contact information, keywords and an abstract.  You will then upload your paper and any attachment files (see for more information http://isl.csee.usf.edu/smcB). In the notes to the editor, please clearly indicate that this paper is for our special issue so that it gets routed correctly. Then a paper number will be generated and returned to you. The site has instructions and/or help buttons on each page. After the submission please send a note to parkbh@ornl.gov with the  title of the paper and the names of the authors.