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General Information
    • ISSN: 2010-3751
    • Frequency: Bimonthly (2012-2016); Quarterly (Since 2017)
    • DOI: 10.18178/IJFCC
    • Editor-in-Chief: Prof. Mohamed Othman
    • Executive Editor: Ms. Cherry L. Chan
    • Abstracting/ Indexing: Google Scholar,  Crossref, Electronic Journals LibraryEI (INSPEC, IET), etc.
    • E-mail:  ijfcc@ejournal.net 
Prof. Mohamed Othman
Department of Communication Technology and Network Universiti Putra Malaysia, Malaysia
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.
IJFCC 2014 Vol.3(3): 168-171 ISSN: 2010-3751
DOI: 10.7763/IJFCC.2014.V3.289

Applying Data Ming to Develop a Warning System of Procurement in Construction

Chun-Ling Ho and Hao-Wen Shih
Abstract—In the knowledge-based economy era, an enterprise need to quickly control and accumulate knowledge in a high-knowledge and complicated market and also use them to establish a proper management and warming system for decision-makers and managements. Procurements always play an important role to increase profit in the organization and an effective procurement system always increases knowledge accumulated and management of procurements as well as further feedback alarm when abnormal procurement happened. The research bases on characteristics of construction industry because of personal procurements as well as long and complicated processes. However, if the procurements could be managed or assisted and conducted by knowledge system, it not only hand over related procurement experiences of construction, but also reduces risk of procurement via effective warming system as well as promotes entire performance and profits of enterprise. Therefore, this project will consolidate software and hardware technology of information to find out association rules in knowledge of procurement between different projects from huge database of procurement by data mining technology and also develop a unique abnormal procurement alarm system for construction industry. It is expected to solve operating problems and achieve purchasing needs as well as fulfill profits expectation.

Index Terms—Construction, procurement, warning system, knowledge management, data mining.

The authors are with the Department of Information Management, University of Kao Yuan, Kaohsiung, Taiwan (e-mail: {clho, t90174}@ cc.kyu.edu.tw).


Cite: Chun-Ling Ho and Hao-Wen Shih, "Applying Data Ming to Develop a Warning System of Procurement in Construction," International Journal of Future Computer and Communication vol. 3, no. 3, pp. 168-171, 2014.

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