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CFP - 2010 International Workshop on Domain Driven Data Mining, Joint with ICDM2010

From: <xhzhu@it.uts.edu.au>
Date: Mon, 26 Jul 2010 14:47:24 +1000
Message-ID: <86634fa6e30ced39006b43fd320f30c9.squirrel@webmail-staff.it.uts.edu.au>
To: www-rdf-interest@w3.org
Call for Papers - DDDM2010
The 2010 International Workshop on Domain Driven Data Mining
URL: http://datamining.it.uts.edu.au/dddm/dddm10/

Sydney, Australia, December 14-17, 2010

to be published by IEEE Computer Society Press (EI indexed)

Submission due: 9 August 2010

In conjunction with the 2010 IEEE International Conference on
Data Mining (ICDM 2010)

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 DDDM2009 joint with ICDM2009 in the US, DDDM2008
joint with ICDM2008 in the Italy, and DDDM2007 with SIGKDD, DDDM2010
welcomes theoretical and applied disseminations that make efforts:
o 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 to benefit
critical domain problems in theory and practice;
o 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;
o to present the applications of domain-driven data mining and
demonstrate how KDD can be effectively deployed to solve complex
practical problems; and
o 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
o Domain-driven data mining methodology and project management
o Domain-driven data mining framework, system support and
infrastructure
(2) Ubiquitous intelligence
o Involvement and integration of human intelligence, domain
intelligence, network intelligence, organizational intelligence
and social intelligence in data mining
o Explicit, implicit, syntactic and semantic intelligence in data
o Qualitative and quantitative domain intelligence
o In-depth patterns and knowledge
o Human social intelligence and animat/agent-based social
intelligence in data mining
o Explicit/direct or implicit/indirect involvement of human
intelligence
o Belief, intention, expectation, sentiment, opinion, inspiration,
brainstorm, retrospection, reasoning inputs in data mining
o Modeling human intelligence, user preference, dynamic
supervision and human-mining interaction
o Involving expert group, embodied cognition, collective
intelligence and Consensus construction in data mining
o Human-centered mining and human-mining interaction
o Formalization of domain knowledge, background and prior
information, meta knowledge, empirical knowledge in data mining
o Constraint, organizational, social and environmental factors in
data mining
o Involving networked constituent information in data mining
o Utilizing networking facilities for data mining
o Ontology and knowledge engineering and management
o Intelligence meta-synthesis in data mining
o Domain driven data mining algorithms
o Social data mining software
(3) Deliverable and evaluation
o Presentation and delivery of data mining deliverables
o Domain driven data mining evaluation system
o Trust, reputation, cost, benefit, risk, privacy, utility and
other issues in data mining
o Post-mining, transfer mining, from mined patterns/knowledge to
operable business rules.
o Knowledge actionability, and integrating technical and business
interestingness
o Reliability, dependability, workability, actionability and
usability of data mining
o Computational performance and actionability enhancement
o Handling inconsistencies between mined and existing domain
knowledge
(4) Enterprise applications
o Dynamic mining, evolutionary mining, real-time stream mining,
and domain adaptation
o Activity, impact, event, process and workflow mining
o Enterprise-oriented, spatio-temporal, multiple source mining
o Domain specific data mining, etc.

Important Dates
August 9, 2010 Due date for full workshop papers
September 20, 2010 Notification of paper acceptance to authors
October 11, 2010 Camera-ready of accepted papers
December 14, 2010 Workshop date

Submission

All papers should be submitted through the ICDM2010 submission system here
(http://wi-lab.com/cyberchair/icdm10/scripts/ws_submit.php). 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'10
Workshop Proceedings published by the IEEE Computer Society Press.

For more information

Please refer to the DDDM2010 website:
http://datamining.it.uts.edu.au/dddm/dddm10/
Received on Thursday, 29 July 2010 07:57:36 GMT

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