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Call for Papers: DMSSP at KDD 06
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Call for Papers: DMSSP at KDD 06
KDD-2006 Workshop on
Data Mining Standards, Services and Platforms (DM-SSP 06)
August 20, 2006
A Workshop at KDD-2006
The Twelfth ACM SIGKDD International Conference on
Knowledge Discovery and Data Mining
August 20-23, 2006
Philadelphia, PA
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Web Site: http://www.ncdm.uic.edu/dm-ssp-06.htm
Workshop Submission Deadline: June 18, 2006
IMPORTANT DATES
June 18, 2006 Deadline for electronic submission papers or
abstracts
July 10, 2006 Notification of accepted presentations
July 20, 2006 Camera Ready Copies Due
August 20, 2006 DM-SSP Workshop
SUBMIT PAPERS TO: connelly@... with the subject line "DM-SSP 06
Workshop submission".
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WORKSHOP DESCRIPTION
DM-SSP `06 is the sixth KDD workshop focusing on standards, services,
and platforms for data mining. Motivating this workshop are a number
of trends, including:
1. A number of standards have matured, including PMML, SQL-based
standards for Data Mining, JDM, CRISP, and OMG CWM for Data
Mining. It is timely to expose these standards to the
community and to gather requirements through position papers
and panels for new versions of these standards.
2. Web services, as well as maturing and emerging data mining
standards, will enable standards-based data mining services
for scoring, modeling, and exploration of data. This workshop
will also include this timely topic.
3. Work in related fields, including data grids, data webs, and
semantic webs is very relevant to data mining but often not
included in KDD per se. This workshop will also provide an
opportunity for work on data mining standards and services in
these areas to be included.
If you are using standards and services to build production data
mining and scoring systems, we encourage you to submit a paper or
abstract to DM-SSP 06. To encourage presentations from industry, we
will accept abstracts for presentations, as well as papers, for
consideration.
WORKSHOP FORMAT
The workshop will consist of both invited and contributed talks. Some
of the invited talks will provide an update on PMML and emerging web
service standards for data mining.
All papers should be submitted by email in pdf format to
connelly@... with the subject line "DM-SSP 06 Workshop submission"
by June 18, 2006. Please use the prescribed formatting guidelines of
KDD (Springer LNCS). The workshop proceedings will be published by
the ACM and distributed during the workshop. They will also be
available on the workshop`s home page. The full version of the
accepted papers will be considered for publication in an edited
proceedings after a second round of reviews, pending approval.
Papers should be no longer than 12 pages (or 5,000 words) inclusive of
all references and figures. All papers must be submitted in either PDF
(preferred) or postscript. Please ensure that any special fonts used
are included in the submitted documents. All papers must be original,
and have not been published elsewhere.
For questions, please email connelly@... with the subject line
"DM-SSP 06 Workshop question".
WORKSHOP TOPICS
Topics appropriate for the workshop include the following topics and
closely related topics.
Standards Based Data Mining Services:
* Scoring services
* Analysis services
* Data exploration services
* Statistical modeling services
Maturing Standards:
* Predictive Model Markup Language (PMML)
* XML for Analysis
* SQL-based standards for data mining
* Java Data Mining (JDM) - Java Specification Request 73 (JSR-73)
* CRoss Industry Standard Process for Data Mining (CRISP-DM)
* OMG Common Warehouse Metadata (CWM) for Data Mining
Related Standards:
* Web services (SOAP/XML, WSRF, etc)
* Grid services (OGSA, etc.)
* Semantic Web Standards (RDF, OWL, etc.)
Emerging Standards:
* Standards for KDD workflow
* Standards for data transformations
* Standards for real time data mining
* Standards for data webs
Open Source Data Mining Platforms:
* R
* Weka
* GNU Octave
ORGANIZING COMMITTEE:
Dave Selinger, FortisForge.com
Robert Grossman, Open Data Group and University of Illinois at Chicago
Rick Pechter, MicroStrategy
Stefan Raspl, IBM
Shirley Connelly, University of Illinois at Chicago
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