[Computational-biology] CFP: 7th IEEE Intl. Conf. on Data Mining (ICDM) Oct 28-31 2007, Omaha, NE, USA

Prithviraj Dasgupta via comp-bio%40net.bio.net (by pdasgupta At mail.unomaha.edu)
Mon Jan 29 12:18:58 EST 2007


(Apologies if you receive multiple copies of this message)

==================================================================
Call for Papers
 
ICDM '07: The 7th IEEE International Conference on Data Mining
 
Sponsored by the IEEE Computer Society 
 
October 28 - 31, 2007 
Embassy Suites Hotel,  Omaha, NE, USA 
  
http://www.ist.unomaha.edu/icdm2007/
 
(Papers Due: Friday June 1st, 2007)
(Submission of title/abstract a week in advance is encouraged; 
  revision of submission is possible until the deadline.)

===================================================================
 
The IEEE International Conference on Data Mining series (ICDM) has 
established itself as the world's premier research conference in data
mining. It provides an international forum for presentation of original 
research results, as well as exchange and dissemination of innovative, 
practical development experiences. The conference covers all aspects of 
data 
mining, including algorithms, software and systems, and applications. In 
addition, ICDM draws researchers and application developers from a wide 
range 
of data mining related areas such as statistics, machine learning, pattern 

recognition, databases and data warehousing, data visualization, 
knowledge-based systems, and high performance computing. By promoting 
novel, 
high quality research findings, and innovative solutions to challenging 
data 
mining problems, the conference seeks to continuously advance the 
state-of-the-art in data mining. Besides the technical program, the 
conference will feature workshops, tutorials, panels and, new for this 
year, 
the ICDM data mining contest.

---------------------------------------------------------------
Topics of Interest
--------------------------------------------------------------- 
 
Topics related to the design, analysis, and implementation of data
mining applications are of interest. These include, but are not limited 
to:

Data mining foundations
  * Novel data mining algorithms in traditional areas (such as 
classification, 
    regression, clustering, probabilistic modeling, and association 
analysis)
  * Algorithms for new, structured, data types, such as arising in 
chemistry, 
     biology, environment, and other scientific domains 
  * Developing a unifying theory of data mining
  * Mining sequences and sequential data
  * Mining spatial and temporal datasets
  * Mining textual and unstructured datasets
  * High performance implementations of data mining algorithms 

  Mining in targeted application contexts
  * Mining high speed data streams 
  * Mining sensor data
  * Distributed data mining and mining multi-agent data
  * Mining in networked settings: web, social and computer networks, and 
online communities 
  * Data mining in electronic commerce, such as recommendation, sponsored
     web search, advertising, and marketing tasks

  Methodological aspects and the KDD process
  * Data pre-processing, data reduction, feature selection, and feature 
    transformation
  * Quality assessment, interestingness analysis, and post-processing
  * Statistical foundations for robust and scalable data mining
  * Handling imbalanced data
  * Automating the mining process and other process related issues 
  * Dealing with cost sensitive data and loss models
  * Human-machine interaction and visual data mining
  * Security, privacy, and data integrity

Integrated KDD applications and systems
  * Bioinformatics, computational chemistry, geoinformatics, and other 
     science & engineering disciplines
  * Computational finance, online trading, and analysis of markets
  * Intrusion detection, fraud prevention, and surveillance
  * Healthcare, epidemic modeling, and clinical research 
  * Customer relationship management
  * Telecommunications, network and systems management
 
---------------------------------------------------------------
Submission
--------------------------------------------------------------- 

High quality papers in all data mining areas are solicited. Original
papers exploring new directions will receive especially careful
consideration. Papers that have already been accepted or are currently 
under 
review for other conferences or journals will not be considered for ICDM 
'07.
 
Paper submissions should be limited to a maximum of 10 pages in the
IEEE 2-column format, the same as the camera-ready format (see the 
IEEE Computer Society Press Proceedings Author Guidelines at
http://www.computer.org/portal/pages/cscps/cps/final/icdm06.xml).
All papers will be reviewed by the Program Committee on the basis of 
technical quality, relevance to data mining, originality,
significance, and clarity. Starting this year, a double blind review 
process
will be adopted. Authors should avoid using identifying information in
the text of the paper. Please use the Submission Form on the ICDM '07 
website to submit your paper.  Accepted papers will be published in the 
conference proceedings by the IEEE Computer Society Press.

All accepted papers will be published in the ICDM'07 proceedings and 
accorded 
oral presentation times in the main conference. Submissions accepted as 
regular papers will be allocated 10 pages in the proceedings. Submissions 
accepted 
as short papers will be allocated 6 pages in the proceedings and will have 
a 
shorter presentation time at the conference than regular papers.

A selected number of IEEE ICDM '07 accepted papers will be invited for
possible inclusion, in expanded and revised form, in the Knowledge 
and Information Systems journal (http://www.cs.uvm.edu/~kais/)
published by Springer-Verlag.

---------------------------------------------------------------
ICDM Best Paper Awards 
---------------------------------------------------------------
 
IEEE ICDM Best Paper Awards will be conferred at the conference on the
authors of (1) the best research paper and (2) the best application
paper. Strong, foundational, results will be considered for the best 
research
paper award and application-oriented submissions will be considered for 
the
best application paper award.
 
--------------------------------------------------------------- 
Workshops
---------------------------------------------------------------

As part of the main conference technical program, ICDM will
continue its tradition of hosting workshops that focus on new
research directions and initiatives. All accepted workshop 
papers will be included in a separate workshop proceedings published 
by the IEEE Computer Society Press.

Please see the ICDM'07 website for solicitations for workshop proposals.

--------------------------------------------------------------- 
Tutorials
---------------------------------------------------------------
 
ICDM will host tutorials covering topics in data mining of interest to
the research community as well as application developers. 
Both short (2 hours) and long (half day) tutorials will be
considered.  The tutorials will be part of the main conference
technical program.

Please see the ICDM'07 website for solicitations for tutorial proposals. 

---------------------------------------------------------------
Important Dates
---------------------------------------------------------------

May 25, 2007  : open for title and abstract submission
June 1st, 2007: deadline for abstract and full paper submission
July 30th, 2007: Notification of acceptance
August 13th, 2007: Camera-ready copy and copyright release form deadline 

Workshop proposal submission: February 12, 2007 
Tutorial proposal submission: July 13, 2007

All paper submissions will be handled electronically. Detailed
instructions are provided on the conference home page at
http://www.ist.unomaha.edu/icdm2007/.

Conference Co-Chairs: 
  * Yong Shi, University of Nebraska at Omaha (USA)
  * Christopher W. Clifton,  Purdue University (USA)

Program Committee Chairs: 
  * Naren Ramakrishnan, Virginia Tech (USA) 
  * Osmar Zaiane, University of Alberta (Canada)

Workshop Chairs:
  * Qiuming Zhu, University of Nebraska at Omaha (USA)
  * Anthony K.H. Tung, National University of Singapore (Singapore)
 
Tutorials Chair: 
  * Jian Pei, Simon Fraser University (Canada)

Panels Chair:
  * Geoffrey I. Webb, Monash Uiversity (Australia)

ICDM Data Mining Contest Chairs:
  * Chris Ding, Lawrence Berkeley National Laboratory (USA) 
  * Gang Kou, Thomson Corporation (USA)
  * Qiang Yang, Hong Kong University of Science and Technology (Hong Kong)

Local Arrangements Chair:
  * Zhengxin Chen, University of Nebraska at Omaha (USA)
  * Hai-Feng Guo, University of Nebraska at Omaha (USA) 

Registration Chair:
  * Parvathi Chundi, University of Nebraska at Omaha (USA)

Publicity Chair:
  * Prithviraj Dasgupta, University of Nebraska at Omaha (USA)
  * Xuelong Li, University of London (UK) 

Finance Chair:
  * Wikil Kwak, University of Nebraska at Omaha (USA)

Sponsorship Chair:
  * Mark Pauley, University of Nebraska at Omaha (USA) 

Proceedings Chair:
  * Xindong Wu, University of Vermont, USA 
 
Program Vice Chairs:
  TBA
 
ICDM Steering Committee:
  * Max Bramer, University of Portsmouth (UK)
  * Nick Cercone, Dalhousie University (Canada)
  * Ramamohanarao Kotagiri, University of Melbourne (Australia) 
  * Vipin Kumar, University of Minnesota (USA)
  * Katharina Morik, University of Dortmund (Germany)
  * Gregory Piatetsky-Shapiro, KDnuggets (USA)
  * Benjamin W. Wah, University of Illinois, Urbana-Champaign (USA) 
  * Xindong Wu (Chair), University of Vermont (USA)
  * Philip S. Yu, IBM T.J. Watson Research Center (USA)
  * Ning Zhong, Maebashi Institute of Technology (Japan)
 


More information about the Comp-bio mailing list