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

From: Yanchang Zhao <zhaoyanchang@hotmail.com>
Date: Tue, 19 May 2009 04:54:35 +0000
Message-ID: <BAY114-W30FB478A2E9E23BE55C5A4C65B0@phx.gbl>
To: www-rdf-interest <www-rdf-interest@w3.org>




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                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 
businesses.

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 
efforts:

- 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.



TOPICS OF INTEREST
==================

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 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 
  mining
- 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



Submission
==========

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

Webmaster
Xuchun Su    University of Technology, Sydney, Australia



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

For more information, please refer to the DDDM2009 website:
http://datamining.it.uts.edu.au/dddm09/

_________________________________________________________________
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Received on Tuesday, 19 May 2009 04:55:17 GMT

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