Title :
S-Canopy:A feature-based clustering algorithm for supplier categorization
Author :
Irfan, Danish ; Xu Xiaofei ; Deng Shengchun ; He, Zengyou ; Ye Yunming
Author_Institution :
Sch. of Comput. Sci.&Technol., Harbin Inst. of Technol., Harbin
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 :
cost reduction; logistics; pattern clustering; supply chain management; S-Canopy clustering; business performance; canopy clustering; data clustering algorithm; feature-based clustering algorithm; logistic cost reduction; supplier categorization; Aggregates; Clustering algorithms; Computer science; Data analysis; Data mining; Delta modulation; Partial response channels; Partitioning algorithms; Raw materials; Supply chain management; Supplier categorization; canopy clustering; data clustering;
Conference_Titel :
Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-2799-4
Electronic_ISBN :
978-1-4244-2800-7
DOI :
10.1109/ICIEA.2009.5138291
