[Elsnet-list] CFP: DDDM 2011 Workshop joint with ICDM 2011, Deadline August 5, Vancouver, Canada

Notice AAI notice at advancedanalytics.org.au
Fri Jul 29 03:16:15 CEST 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:                   August 5, 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
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