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Special Sessions All
special sessions are open to attendees of
all conferences held at WORLDCOMP'14.
The following special sessions are approved
and will be hosted by DMIN'14:
1)
Real-World Data Mining Applications, Challenges, and
Perspectives
2) Data Mining Applications for
Advanced Manufacturing
Special Session on
Real-World Data Mining
Applications, Challenges, and Perspectives
Call for Papers (Special Session)
Organizer:
Dr.
Mahmoud Abou-Nasr, Ford Motor Company
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Research and Innovation Center,
mabounas@ford.com
The
past decade has witnessed a vast growth of the amount of
data produced and the proliferation of specialized
databases in a wide range of business, industrial,
medical and scientific applications. Data mining is
becoming an increasingly important tool in the process
of knowledge discovery and the transformation of data
into valuable information. The objective of this special
session is to provide a forum for the data mining
researchers and industrial practitioners to discuss data
mining applications, issues, and the challenges that
arise when addressing real-world problems.
Topics of interest
include, but are not limited to:
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Enterprise knowledge management/knowledge discovery
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Corporate planning
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Direct marketing
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Credit scoring
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Forecasting
-
Automotive applications
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Medical decision making, diagnostics
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Bioinformatics
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Text and image recognition
Challenges to be addressed include but are not limited
to:
This special session of DMIN'14
will cover all aspects of
data mining applications. The special session will be
held during the DMIN'14 conference, July 21-24, in Las
Vegas, Nevada, USA. All papers should be
submitted using the standard procedures for DMIN papers.
For your submission of the draft paper, please select
the Track 'RWDMA
-
Special Session on Real-World Data Mining Applications,
Challenges, and Perspectives'.
Any questions should be directed to
the
special session organizer or to one of the DMIN
conference organizers.
 |
Download
CfP Special
Session on Real-World Data Mining Applications,
Challenges, and Perspectives(pdf) |
Special Session on Data Mining
Applications for Advanced Manufacturing
Call for Papers (Special Session)
Organizer: David Baglee, Department for Computing,
Engineering and Technology, University of Sunderland,
UK,
David.Baglee@sunderland.ac.uk
Data mining applications
are becoming increasingly important for the wide range
of manufacturing processes. During daily manufacturing
operations large amounts of data is generated. The
abundance of data, however, often impedes the ability to
extract useful knowledge. In addition, the large amount
of data stored in often unconnected databases makes it
impractical to manually analyze for valuable
decision-making information. New intelligent Data Mining
tools and techniques are required which can
intelligently analyze data and produce useful knowledge
for manufacturing.
The objective of the
special session is to provide a forum for data mining
researchers and manufacturing specialists /
practitioners from industry to discuss and present data
mining applications and challengers that arise when
developing, implementing and using data mining for real
world manufacturing applications.
Topics will include, but are not limited to:
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Knowledge Management
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New data mining technologies
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Product design and development
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Asset Management / Computerized Maintenance
Management Systems
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Intelligent data mining systems for manufacturing
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Production Planning
The special session will be held during the DMIN
conference, July 21-24, 2014, in Las Vegas, Nevada, USA.
All papers should be
submitted using the standard procedures for DMIN papers.
For your submission of the draft paper, please select
the Track 'DMAAM - Data Mining Applications for Advanced
Manufacturing'. Any questions should be directed to
the
special session organizer or to one of the DMIN
conference organizers.
[see also the Invited
Talk by Diego Galar: Big Data Issues for Mining
Knowledge in Maintenance Information Systems [more]]
 |
Download
CfP Special
Session on Data Mining Applications for Advanced
Manufacturing(pdf) |
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