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Call for Papers - DDDM2011
The Fifth International
Workshop on Domain Driven Data
Mining
In conjunction with the 2011
IEEE International Conference on
Data Mining (ICDM 2011)
December 11-14, 2011,
Vancouver, Canada
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 from
DDDM2007 to DDDM2010, DDDM2011
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
July 23, 2011:
Due date for full
workshop papers
September 20, 2011:
Notification of paper
acceptance to authors
October 11, 2011:
Camera-ready of
accepted papers
December 10, 2011:
Workshop date
Submission
All papers should be submitted
through the ICDM2011 submission
system here by directing to
DDDM2011 workshop. 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