DDDM 2009 - DDDM 2009 The 3rd International Workshop on Domain Driven Data Mining

Website http://datamining.it.uts.edu.au/dddm09 | Edit Freely

Category DDDM 2009

Deadline: July 17, 2009 | Date: December 06, 2009

Venue/Country: Florida, U.S.A

Updated: 2010-06-04 19:32:22 (GMT+9)

Call For Papers - CFP

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/