| Mining multimedia data |
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IBM Centre for Advanced Studies Conference
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Proceedings of the 1998 conference of the Centre for Advanced Studies on Collaborative research
table of contents
Toronto, Ontario, Canada
Page: 24
Year of Publication: 1998
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Authors
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Osmar R. Zaïane
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Intelligent Database Systems Research Laboratory, School of Computing Science, Simon Fraser University, Burnaby, BC, Canada V5A 1S6
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Jiawei Han
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Intelligent Database Systems Research Laboratory, School of Computing Science, Simon Fraser University, Burnaby, BC, Canada V5A 1S6
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Ze-Nian Li
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Intelligent Database Systems Research Laboratory, School of Computing Science, Simon Fraser University, Burnaby, BC, Canada V5A 1S6
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Jean Hou
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Intelligent Database Systems Research Laboratory, School of Computing Science, Simon Fraser University, Burnaby, BC, Canada V5A 1S6
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IBM Press
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| Bibliometrics |
Downloads (6 Weeks): 25, Downloads (12 Months): 159, Citation Count: 5
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ABSTRACT
Data Mining is a young but flourishing field. Many algorithms and applications exist to mine different types of data and extract different types of knowledge. Mining multimedia data is, however, at an experimental stage.We have implemented a prototype for mining high-level multimedia information and knowledge from large multimedia databases. MultiMedia Miner has been designed based on our years of experience in the research and development of a relational data mining system, DBMiner, in the Intelligent Database Systems Research Laboratory, and a Content-Based Image Retrieval system from Digital Libraries, C-BIRD, in the Vision and Media Laboratory.MultiMediaMiner includes the construction of multimedia data cubes which facilitate multiple dimensional analysis of multimedia data, and the mining of multiple kinds of knowledge, including summarization, classification, and association, in image and video databases. The images and video clips used in our experiments are collected by crawling the WWW. Many challenges have yet to be overcome, such as the large number of dimensions, and the existence of multi-valued dimensions.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 5
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B. Vassiliadis , A. Stefani , L. Drossos , K. Ioannou, Knowledge discovery in multimedia repositories: the role of metadata, Proceedings of the 7th WSEAS International Conference on Mathematical Methods and Computational Techniques In Electrical Engineering, p.330-335, October 27-29, 2005, Sofia, Bulgaria
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INDEX TERMS
Primary Classification:
H.
Information Systems
H.2
DATABASE MANAGEMENT
H.2.8
Database applications
Subjects:
Data mining
Additional Classification:
H.
Information Systems
H.2
DATABASE MANAGEMENT
H.2.4
Systems
Subjects:
Multimedia databases
H.2.8
Database applications
Subjects:
Image databases
H.5
INFORMATION INTERFACES AND PRESENTATION (I.7)
H.5.1
Multimedia Information Systems
Subjects:
Video (e.g., tape, disk, DVI)
General Terms:
Algorithms,
Design,
Experimentation,
Measurement,
Performance,
Theory
Keywords:
data cube,
data mining,
data warehousing,
image analysis,
information retrieval,
multimedia,
world-wide web
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