DocumentCode
554003
Title
Notice of Retraction
A hyper SVM model for multiple classifications
Author
Fong-Ming Shyu ; Hsiang-Yuen Liao
Author_Institution
Dept. of Multimedia Design, Nat. Taichung Inst. of Technol., Taichung, Taiwan
Volume
1
fYear
2011
fDate
26-28 July 2011
Firstpage
340
Lastpage
343
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In this paper, we proposed a Binary-Tree as a hyper model for Support Vector Machine (SVM) to achieve multiple classifications. It is well-known that SVM can be properly used for two-way classification. We applied SVM to a Blog template recommendation system in previous study and used radix sort mechanism to solve multiple classifications. But, there is still a problem that how can we decide which parameter order can be changed to reproduce a new classification. So, we constructed a hyper SVM model to solve this problem for the original SVM model. This model is included a Huffman-Tree like mechanism, called hyper SVM. Finally, we demonstrated how this enhanced SVM model to solve multiple classifications within our previous study.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In this paper, we proposed a Binary-Tree as a hyper model for Support Vector Machine (SVM) to achieve multiple classifications. It is well-known that SVM can be properly used for two-way classification. We applied SVM to a Blog template recommendation system in previous study and used radix sort mechanism to solve multiple classifications. But, there is still a problem that how can we decide which parameter order can be changed to reproduce a new classification. So, we constructed a hyper SVM model to solve this problem for the original SVM model. This model is included a Huffman-Tree like mechanism, called hyper SVM. Finally, we demonstrated how this enhanced SVM model to solve multiple classifications within our previous study.
Keywords
Web sites; information filtering; support vector machines; Huffman-tree like mechanism; binary-tree; blog template recommendation system; hyper SVM model; multiple classifications; radix sort mechanism; support vector machine; Binary trees; Blogs; Cascading style sheets; Support vector machines; Testing; Training; Transforms; B-Tree; Classification; SVM;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location
Shanghai
ISSN
2157-9555
Print_ISBN
978-1-4244-9950-2
Type
conf
DOI
10.1109/ICNC.2011.6022109
Filename
6022109
Link To Document