CFP: DDDM 2011 Workshop joint with ICDM 2011, Deadline July 23, Vancouver, Canada

[DDDM 2011]

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Call for Papers ***Apologies for cross-posting***

The 5th International Workshop on Domain Driven Data Mining (DDDM)
In conjunction with the 2011 IEEE International Conference on Data
Mining (ICDM 2011)
December 11-14, 2011, Vancouver, Canada

http://datamining.it.uts.edu.au/dddm/dddm11/ 
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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 businesses.

All papers accepted by the workshop will be included in the ICDM'10
Workshop Proceedings published by the IEEE Computer Society Press.  

* Important Dates:
* Submission Deadline: July 23, 2011
* Notification of Acceptance: September 20, 2011
* Camera Ready Submission Due: October 11, 2011

Topics:
This workshop solicits original theoretical and practical research on
the following topics. 
(1) Methodologies and infrastructure 
* Domain-driven data mining methodology and project management
* Domain-driven data mining framework, system support and
infrastructure
(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
intelligence
* 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 mining
* Constraint, organizational, social and environmental factors in data
mining
* Involving networked constituent information in data mining
* 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/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 mining
* Domain specific data mining, etc.

Keynote Speaker:
* Jian Pei, Simon Fraser University


Organizing Committee:
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* General chair:
- Phillips Yu, University of Illinois at Chicago

* PC co-chairs:
- Wei Fan, IBM T.J. Watson Research
- Wolfgang Nejdl, L3S Research Center, University of Hannover
- Ling Chen, University of Technology Sydney