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MDMM 2008: 2nd International Workshop on Multimedia Data
Mining and Management
September 2, Turin, Italy
in conjunction with
19th International Conference on DEXA 2008 |
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(New) The workshop will be held as
followings (Accepted
Paper and Final Program Program).
- 9:00 AM ~ 1:00 PM, September 2, 2008 (Tuesday)
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Changed Important Dates
Notification Date: April 25, 2008
May 4, 2008
Final Version of Accepted Papers: May 16, 2008
May 23, 2008 |
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The deadlines are extended:
Abstract due: March 14, 2008
March 28, 2008
Full Paper due: March 28, 2008
April 4, 2008 |
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Jan 14, 2008:
Submission web site is OPEN. Please upload abstract (no more
than 250 words in ASCII text) and paper at
https://www.dexa.org/dexadriver/ |
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Workshop Title |
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MDMM 2008: 2nd International Workshop on Multimedia Data Mining
and Management |
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Workshop description and objective |
With the recent advances in electronic imaging, video
devices, storage, networking and computer power, the amount of
multimedia has grown enormously, and data mining has become a
popular way of discovering new knowledge from such a large data
sets. Multimedia data mining is a discipline which brings
together database systems, artificial intelligence, and
multimedia processing, such as image and video processing. It is
important to understand what is multimedia data mining, how data
mining techniques can contribute to discover new knowledge, how
to organize and manage the discovered knowledge and concepts.
The multimedia data appear in multiple forms including audio,
speech, text, web, image, video and combinations of several
types.
In this workshop, we aim to solicit papers that address the
technical challenges in mining multimedia data and management.
Through the workshop, we expect to bring together experts in
analysis of multimedia data, state-of-art data mining and
knowledge discovery in multimedia database systems, and domain
experts in diverse areas, such as medical, surveillance, and
education.
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| Topics |
Topics of contributions
include (but are not limited to):
Algorithms and Models
• Association rules for multimedia data mining
• Clustering algorithms for multimedia data mining
• Classification algorithms for multimedia data mining
• Conceptual clustering for multimedia data mining
• Neural networks for multimedia data mining
• Parallel and distributed data mining for multimedia data
• Multimedia data mining in pervasive computing
• Multimedia ontology
• Stream data mining algorithms
• Spatio-Temporal data mining and algorithms
Applications
• Audio/Image/Video DBMSs
• Data mining system for medical multimedia data
• Multimedia segmentation
• Visualization
• Semantic web and annotation
• Summarization and abstraction
• Video abstraction
• Contents-based image/video retrieval systems
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