CFP - 2010 International Workshop on Domain Driven Data Mining, Joint with ICDM2010
Date: Mon, 26 Jul 2010 03:47:49 -0700 (PDT)
Message-ID: <24369a41-9d45-4b4b-a185-00454c9f1fb5_at_m17g2000prl.googlegroups.com>
Call for Papers - ICDM-DDDM2010
The 2010 ICDM Workshop on Domain Driven Data Mining URL: http://datamining.it.uts.edu.au/dddm/dddm10/
In conjunction with the 2010 IEEE International Conference on Data Mining (ICDM 2010)
Sydney, Australia, December 14-17, 2010
- Accepted papers to be published by IEEE Computer Society Press (EI indexed)
- Invited talk by Prof Bing Liu, University of Illinois at Chicago
- Invited talk by Dr Wei Fan, IBM (to be confirmed)
- Feature talk on Social Security Data Mining
Submission due: August 9, 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 Mon Jul 26 2010 - 12:47:49 CEST