2nd CFP - DDDM 2009 Workshop, in conjunction with ICDM'09 - due by July 17, 2009■

             2nd Call for Papers - DDDM 2009
The 3rd International Workshop on Domain Driven Data Mining
          Miami, Florida, USA, December 6, 2009
            In conjunction with IEEE ICDM'09
       URL: http://datamining.it.uts.edu.au/dddm09/

The Workshop on Domain Driven Data Mining (DDDM) series
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 data-centered hidden pattern mining
to domain-driven actionable knowledge delivery in varying
data mining domains toward supporting smart decision and

Following the success of DDDM2007 joint with SIGKDD2007 in
the US and DDDM2008 joint with ICDM2008 in Italy, DDDM2009
welcomes theoretical and applied disseminations that make

- to design next-generation data mining methodology for
  actionable knowledge discovery and delivery, toward
  handling critical issues for KDD to effectively and
  efficiently contribute to real-world smart businesses and
  smart decision and benefit critical domain problems in
  theory and practice;

- to devise domain-driven data mining techniques to bridge
  the gap between a converted problem and its actual
  business problem, between academic objectives and
  business goals, between technical significance and
  business interest, and between identified patterns and
  business expected deliverables, toward strengthening
  business intelligence in complex enterprise applications;

- to present the applications of domain-driven data mining
  and demonstrate how KDD can be effectively deployed to
  solve complex practical problems; and

- to identify challenges and future directions for data
  mining research and development in the dialogue between
  academia and industry.


This workshop solicits original theoretical and practical
research on the following topics.

(1) Methodologies and infrastructure
- Domain-driven data mining methodology and project
- Domain-driven data mining framework, system support and

(2) Ubiquitous intelligence
- Involvement and integration of human intelligence, domain
  intelligence, network intelligence, organizational
  intelligence and social intelligence in data mining
- Explicit, implicit, syntactic and semantic intelligence
  in data
- Qualitative and quantitative domain intelligence
- In-depth patterns and knowledge
- Human social intelligence and animat/agent-based social
  intelligence in data mining
- Explicit/direct or implicit/indirect involvement of human
- Belief, intention, expectation, sentiment, opinion,
  inspiration, brainstorm, retrospection, reasoning inputs
  in data mining
- Modeling human intelligence, user preference, dynamic
  supervision and human-mining interaction
- Involving expert group, embodied cognition, collective
  intelligence and consensus construction in data mining
- Human-centered mining and human-mining interaction
- Formalization of domain knowledge, background and prior
  information, meta knowledge, empirical knowledge in data
- Constraint, organizational, social and environmental
  factors in data mining
- Involving networked constituent information in data
- Utilizing networking facilities for data mining
- Ontology and knowledge engineering and management
- Intelligence meta-synthesis in data mining
- Domain driven data mining algorithms
- Social data mining software

(3) Deliverable and evaluation
- Presentation and delivery of data mining deliverables
- Domain driven data mining evaluation system
- Trust, reputation, cost, benefit, risk, privacy, utility
  and other issues in data mining
- Post-mining, transfer mining, from mined patterns and
  knowledge to operable business rules.
- Knowledge actionability, and integrating technical and
  business interestingness
- Reliability, dependability, workability, actionability
  and usability of data mining
- Computational performance and actionability enhancement
- Handling inconsistencies between mined and existing
  domain knowledge

(4) Enterprise applications
- Dynamic mining, evolutionary mining, real-time stream
  mining, and domain adaptation
- Activity, impact, event, process and workflow mining
- Enterprise-oriented, spatio-temporal, multiple source
- Domain specific data mining, etc.

Important Dates

July 17, 2009     Due date for full workshop papers
Sept. 8, 2009     Notification of paper acceptance
Sept. 28, 2009     Camera-ready of accepted papers
Dec. 6, 2009    Workshop date


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). All papers will be reviewed
by the Program Committee on the basis of technical quality,
relevance to domain driven data mining, originality,
significance and clarity.

All papers accepted for the workshop will be included in
the ICDM'09 Workshop Proceedings published by the IEEE
Computer Society Press. Selected papers from the workshop
will be invited for consideration of publication in a
special issue of a SCI-indexed journal to be confirmed.

Organizing Committee

General Chair
Philip S Yu     University of Illinois at Chicago, USA

Workshop Chairs
Longbing Cao    University of Technology, Sydney, Australia
Jean-Francois Boulicaut    University of Lyon, France
Shusaku Tsumoto    Shimane University, Japan

Organizing Chair
Yanchang Zhao    University of Technology, Sydney, Australia

Xuchun Su    University of Technology, Sydney, Australia

Inquiries can be forwarded to kdd(at)it.uts.edu.au.

For more information, please refer to the DDDM2009 website:

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Received on Saturday, 13 June 2009 00:09:01 UTC