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MDMM 2013: 4th International Workshop on Multimedia Data
Mining and Management
August 26 ~ 30, 2013, Prague, Czech
Republic
in conjunction with
24th International Conference on DEXA 2013 |
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- The deadline for the abstract
and full paper submissions have been extended as follows:
== Extended deadline for Submission ==
New Abstract and Full Paper Submission: April 14, 2013
- [New: Jan 15, 2013]
Submission website is now open:
https://confdriver.ifs.tuwien.ac.at/dexa2013/home/323
- MDMM website is now open
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Workshop Title |
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MDMM 2013: 4th 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 a large data set
including database, social media data and big data. 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
- Social media data mining
- Big data analytics for multimedia data
- Natural User Interface of multimedia data, such as
Kinect device
- 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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