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Call for Papers
2007 ACM SIGKDD Workshop on Domain Driven Data Mining (DDDM 2007)
San Jose, California, USA, 12th August 2007
In conjunction with ACM SIGKDD International Conference on
Knowledge Discovery and Data Mining (KDD'07)
URL: http://datamining.it.uts.edu.au/dddm/
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The "2007 ACM SIGKDD Workshop on Domain Driven Data Mining (DDDM2007)" aims
to provide a premier forum for sharing findings, knowledge, insight,
experience
and lessons in tackling potential challenges in discovering actionable
knowledge
from complex domain problems, promoting interaction and filling the gap
between
academia and business, and driving a paradigm shift from interesting hidden
pattern mining to actionable knowledge discovery in varying data mining
domains.
The workshop welcomes theoretical and applied disseminations that make
efforts
(1) to expose next-generation data mining methodology for actionable
knowledge
discovery, identifying how KDD techniques can better contribute to critical
domain problems in theory and practice; (2) to uncover domain-driven data
mining
techniques identifying how KDD can better strengthen business
intelligence in
complex enterprise applications; (3) to disclose the applications of
domain-driven data mining identifying how KDD can be effectively
deployed into
solving complex practical problems; and (4) to identify challenges and
directions for future research and development in the dialogue between
academia
and business.
Topics
------
The SIGKDD DDDM2007 Workshop solicits original theoretical and practical
research
on topics including, but not limited to, the following aspects:
* Domain-driven data mining methodology and project management
* Domain-driven KDD infrastructure and system support
* Knowledge actionability and actionable knowledge discovery framework *
Involvement of human intelligence, domain intelligence, web intelligence *
Mining in-depth patterns and deep data intelligence
* Intelligence meta-synthesis in KDD
* Human-centered mining and human-mining interaction
* Activity, impact, event, process and workflow mining
* Unbalanced, constraint, dynamic and stream mining
* Reliability, trust, privacy, utility, issues in data mining
* Enterprise-oriented, spatio-temporal, multiple source mining
* Ontology and knowledge engineering and management
* Computational performance and actionability enhancement
* Domain specific mining such as security mining, bioinformatic mining, etc.
Submission Instructions
-----------------------
Interested authors should submit their papers as an email attachment to the
Co-Chair (kdd at it.uts.edu.au) of the ACM SIGKDD Workshop on Domain
Driven Data
Mining (DDDM 2007). Submissions should be prepared using the standard ACM
format
(http://www.acm.org/sigs/pubs/proceed/template.html) in MS Word or PDF
format.
Manuscripts must not exceed 10 pages, and present a cover page which should
include the paper title, author(s), authors' affiliations, e-mail addresses,
contact numbers, postal address, and an abstract.
Important dates
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Submission of Papers: May 20, 2007
Notification: June 20, 2007
Camera Ready: July 10, 2007
Half-day Workshop Presentation: August 12, 2007
Publication Plans
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The workshop proceeding will be made available in the workshop and online.
Selected papers from the workshop will be invited for consideration of
publication in a special issue of a leading related journal and as a book
chapter by Springer (to be confirmed). Some of the selected papers will be
considered to be published in the Trends & Controversies department in
IEEE
Intelligent Systems magazine (www.computer.org/intelligent). Details of the
special issue and book publication will be announced on the workshop website
later.
Organizing Committee
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General Chair
Philips Yu, IBM T.J. Watson Research Center, USA
Workshop Chairs
Chengqi Zhang, University of Technology, Sydney, Australia
Graham Williams, Australian Taxation Office, Australia
Longbing Cao, University of Technology, Sydney, Australia
Organizing Chair
Yanchang Zhao, University of Technology, Sydney, Australia
Webmaster
Chao Luo, University of Technology, Sydney, Australia
Contact
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For general questions: Longbing Cao (lbcao from it.uts.edu.au)
For paper submission: Yanchang Zhao (yczhao from it.uts.edu.au)
For website: Chao Luo (chaoluo from it.uts.edu.au)