S-canopy: A feature-based clustering algorithm for supplier categorization

Danish Irfan; Xu Xiaofei; Deng Shengchun; Zengyou He; Ye Yunming

doi:10.1109/ICIEA.2009.5138291

S-canopy: A feature-based clustering algorithm for supplier categorization

Danish Irfan^*
, Xu Xiaofei
, Deng Shengchun
, Zengyou He
, Ye Yunming

^*Corresponding author for this work

School of Computer Science and Technology, Harbin Institute of Technology
Hong Kong University of Science and Technology
Harbin Institute of Technology Shenzhen

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

4 Scopus citations

Abstract

Supplier categorization is considered as a business approach to reduce the logistic costs and improve business performance. In this work we propose a data clustering algorithm for supplier categorization namely S-Canopy clustering. It is simply making use of canopy clustering to reduce the number of distance comparisons. Comparison analysis shows a feasibility to obtain better results for categorization of suppliers in a supplier base.

Original language	English
Title of host publication	2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009
Pages	677-681
Number of pages	5
DOIs	https://doi.org/10.1109/ICIEA.2009.5138291
State	Published - 2009
Externally published	Yes
Event	2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009 - Xi'an, China Duration: 25 May 2009 → 27 May 2009

Publication series

Name	2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009

Conference

Conference	2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009
Country/Territory	China
City	Xi'an
Period	25/05/09 → 27/05/09

Keywords

Canopy clustering
Data clustering
Supplier categorization

Access to Document

10.1109/ICIEA.2009.5138291

Cite this

Irfan, D., Xiaofei, X., Shengchun, D., He, Z., & Yunming, Y. (2009). S-canopy: A feature-based clustering algorithm for supplier categorization. In 2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009 (pp. 677-681). Article 5138291 (2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009). https://doi.org/10.1109/ICIEA.2009.5138291

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title = "S-canopy: A feature-based clustering algorithm for supplier categorization",

abstract = "Supplier categorization is considered as a business approach to reduce the logistic costs and improve business performance. In this work we propose a data clustering algorithm for supplier categorization namely S-Canopy clustering. It is simply making use of canopy clustering to reduce the number of distance comparisons. Comparison analysis shows a feasibility to obtain better results for categorization of suppliers in a supplier base.",

keywords = "Canopy clustering, Data clustering, Supplier categorization",

author = "Danish Irfan and Xu Xiaofei and Deng Shengchun and Zengyou He and Ye Yunming",

year = "2009",

doi = "10.1109/ICIEA.2009.5138291",

language = "英语",

isbn = "9781424428007",

series = "2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009",

pages = "677--681",

booktitle = "2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009",

note = "2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009 ; Conference date: 25-05-2009 Through 27-05-2009",

}

Irfan, D, Xiaofei, X, Shengchun, D, He, Z & Yunming, Y 2009, S-canopy: A feature-based clustering algorithm for supplier categorization. in 2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009., 5138291, 2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009, pp. 677-681, 2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009, Xi'an, China, 25/05/09. https://doi.org/10.1109/ICIEA.2009.5138291

S-canopy: A feature-based clustering algorithm for supplier categorization. / Irfan, Danish; Xiaofei, Xu; Shengchun, Deng et al.
2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009. 2009. p. 677-681 5138291 (2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009).

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

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AU - Irfan, Danish

AU - Xiaofei, Xu

AU - Shengchun, Deng

AU - He, Zengyou

AU - Yunming, Ye

PY - 2009

Y1 - 2009

N2 - Supplier categorization is considered as a business approach to reduce the logistic costs and improve business performance. In this work we propose a data clustering algorithm for supplier categorization namely S-Canopy clustering. It is simply making use of canopy clustering to reduce the number of distance comparisons. Comparison analysis shows a feasibility to obtain better results for categorization of suppliers in a supplier base.

AB - Supplier categorization is considered as a business approach to reduce the logistic costs and improve business performance. In this work we propose a data clustering algorithm for supplier categorization namely S-Canopy clustering. It is simply making use of canopy clustering to reduce the number of distance comparisons. Comparison analysis shows a feasibility to obtain better results for categorization of suppliers in a supplier base.

KW - Canopy clustering

KW - Data clustering

KW - Supplier categorization

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U2 - 10.1109/ICIEA.2009.5138291

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M3 - 会议稿件

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T3 - 2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009

SP - 677

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BT - 2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009

Y2 - 25 May 2009 through 27 May 2009

ER -

S-canopy: A feature-based clustering algorithm for supplier categorization

Abstract

Publication series

Conference

Keywords

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