A multiclass classification tool using cloud computing architecture

Chia Ping Shen; Chia Hung Liu; Feng Sheng Lin; Han Lin; Chi Ying F. Huang; Cheng Yan Kao; Feipei Lai; Jeng Wei Lin

doi:10.1109/ASONAM.2012.139

A multiclass classification tool using cloud computing architecture

Chia Ping Shen^*, Chia Hung Liu, Feng Sheng Lin, Han Lin, Chi Ying F. Huang, Cheng Yan Kao, Feipei Lai, Jeng Wei Lin

^*Corresponding author for this work

Institute of Biopharmaceutical Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Multiclass classification is an important technique to many complex biomedicine problems. Genetic algorithms (GA) are proven to be effective to select features prior to multiclass classification by support vector machines (SVM). However, their use is computation intensive. Based on SOA (Service Oriented Architecture) design principles, this paper proposes a cloud computing framework that exploits the inherent parallelism of GA-SVM classification to speed up the work. The performance evaluations on an mRNA benchmark cancer dataset have shown the effectiveness and efficiency of the framework. With a user-friendly web interface, the framework provides researchers an easy way to investigate the unrevealed secrets in the fast-growing repository of biomedical data.

Original language	English
Title of host publication	Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012
Pages	765-770
Number of pages	6
DOIs	https://doi.org/10.1109/ASONAM.2012.139
State	Published - 2012
Event	2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012 - Istanbul, Turkey Duration: 26 Aug 2012 → 29 Aug 2012

Publication series

Name	Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012

Conference

Conference	2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012
Country/Territory	Turkey
City	Istanbul
Period	26/08/12 → 29/08/12

Keywords

Cloud computing
Feature selection
Genetic algorithm
Multiclass classification
Support vector machine
mRNA

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/ASONAM.2012.139

Cite this

Shen, C. P., Liu, C. H., Lin, F. S., Lin, H., Huang, C. Y. F., Kao, C. Y., Lai, F., & Lin, J. W. (2012). A multiclass classification tool using cloud computing architecture. In Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012 (pp. 765-770). Article 6425667 (Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012). https://doi.org/10.1109/ASONAM.2012.139

Shen, Chia Ping ; Liu, Chia Hung ; Lin, Feng Sheng et al. / A multiclass classification tool using cloud computing architecture. Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012. 2012. pp. 765-770 (Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012).

@inproceedings{eeb7838418f749b6ae8f04cc5265d791,

title = "A multiclass classification tool using cloud computing architecture",

abstract = "Multiclass classification is an important technique to many complex biomedicine problems. Genetic algorithms (GA) are proven to be effective to select features prior to multiclass classification by support vector machines (SVM). However, their use is computation intensive. Based on SOA (Service Oriented Architecture) design principles, this paper proposes a cloud computing framework that exploits the inherent parallelism of GA-SVM classification to speed up the work. The performance evaluations on an mRNA benchmark cancer dataset have shown the effectiveness and efficiency of the framework. With a user-friendly web interface, the framework provides researchers an easy way to investigate the unrevealed secrets in the fast-growing repository of biomedical data.",

keywords = "Cloud computing, Feature selection, Genetic algorithm, Multiclass classification, Support vector machine, mRNA",

author = "Shen, {Chia Ping} and Liu, {Chia Hung} and Lin, {Feng Sheng} and Han Lin and Huang, {Chi Ying F.} and Kao, {Cheng Yan} and Feipei Lai and Lin, {Jeng Wei}",

year = "2012",

doi = "10.1109/ASONAM.2012.139",

language = "English",

isbn = "9780769547992",

series = "Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012",

pages = "765--770",

booktitle = "Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012",

note = "2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012 ; Conference date: 26-08-2012 Through 29-08-2012",

}

Shen, CP, Liu, CH, Lin, FS, Lin, H, Huang, CYF, Kao, CY, Lai, F & Lin, JW 2012, A multiclass classification tool using cloud computing architecture. in Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012., 6425667, Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012, pp. 765-770, 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012, Istanbul, Turkey, 26/08/12. https://doi.org/10.1109/ASONAM.2012.139

A multiclass classification tool using cloud computing architecture. / Shen, Chia Ping; Liu, Chia Hung; Lin, Feng Sheng et al.
Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012. 2012. p. 765-770 6425667 (Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Shen, Chia Ping

AU - Liu, Chia Hung

AU - Lin, Feng Sheng

AU - Lin, Han

AU - Huang, Chi Ying F.

AU - Kao, Cheng Yan

AU - Lai, Feipei

AU - Lin, Jeng Wei

PY - 2012

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N2 - Multiclass classification is an important technique to many complex biomedicine problems. Genetic algorithms (GA) are proven to be effective to select features prior to multiclass classification by support vector machines (SVM). However, their use is computation intensive. Based on SOA (Service Oriented Architecture) design principles, this paper proposes a cloud computing framework that exploits the inherent parallelism of GA-SVM classification to speed up the work. The performance evaluations on an mRNA benchmark cancer dataset have shown the effectiveness and efficiency of the framework. With a user-friendly web interface, the framework provides researchers an easy way to investigate the unrevealed secrets in the fast-growing repository of biomedical data.

AB - Multiclass classification is an important technique to many complex biomedicine problems. Genetic algorithms (GA) are proven to be effective to select features prior to multiclass classification by support vector machines (SVM). However, their use is computation intensive. Based on SOA (Service Oriented Architecture) design principles, this paper proposes a cloud computing framework that exploits the inherent parallelism of GA-SVM classification to speed up the work. The performance evaluations on an mRNA benchmark cancer dataset have shown the effectiveness and efficiency of the framework. With a user-friendly web interface, the framework provides researchers an easy way to investigate the unrevealed secrets in the fast-growing repository of biomedical data.

KW - Cloud computing

KW - Feature selection

KW - Genetic algorithm

KW - Multiclass classification

KW - Support vector machine

KW - mRNA

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BT - Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012

T2 - 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012

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Shen CP, Liu CH, Lin FS, Lin H, Huang CYF, Kao CY et al. A multiclass classification tool using cloud computing architecture. In Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012. 2012. p. 765-770. 6425667. (Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012). doi: 10.1109/ASONAM.2012.139

A multiclass classification tool using cloud computing architecture

Abstract

Publication series

Conference

Keywords

UN SDGs

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