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Published Articles >> Table of Contents >> Abstract
21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07)
pp. 335-340
Effectiveness of Multi-Perspective Representation Scheme on Support Vector Machines
Jia Zeng, University of Calgary, Canada
Reda Alhajj, University of Calgary, Canada; Global University, Lebanon
Full Article Text:
 
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AINAW.2007.163
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| Abstract |
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In this paper, we present a multi-perspective representation (MPR) method, which takes advantage of the synergy of multiple representations of an information object. We have provided a detailed description of how to integrate the MPR scheme with support vector machines (MPR-SVM). The results of the experiments conducted on two benchmark data sets have shown the applicability and effectiveness of using the MPR-SVM scheme for classification purposes.
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 Additional Information
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Index Terms- support vector machine, classification, multi-perspective representation method.
Citation:
Jia Zeng, Reda Alhajj,
"Effectiveness of Multi-Perspective Representation Scheme on Support Vector Machines,"
ainaw,
pp. 335-340,
21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07),
2007
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