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Published Articles >> Table of Contents >> Abstract
2006 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops
pp. 23-26
Exploiting Data Mining Techniques for Improving the Efficiency of a Supply Chain Management Agent
Andreas L. Symeonidis, Aristotle University of Thessaloniki, Greece; Informatics and Telematics Institute/CERTH, Greece
Vivia Nikolaidou, Aristotle University of Thessaloniki, Greece
Pericles A. Mitkas, Aristotle University of Thessaloniki, Greece; Informatics and Telematics Institute/CERTH, Greece
Full Article Text:
 
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/WI-IATW.2006.69
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| Abstract |
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Supply Chain Management (SCM) environments are
often dynamic markets providing a plethora of
information, either complete or incomplete. It is,
therefore, evident that such environments demand
intelligent solutions, which can perceive variations and
act in order to achieve maximum revenue. To do so, they
must also provide some sophisticated mechanism for
exploiting the full potential of the environments they
inhabit. Advancing on the way autonomous solutions
usually deal with the SCM process, we have built a robust
and highly-adaptable mechanism for efficiently dealing
with all SCM facets, while at the same time incorporating
a module that exploits data mining technology in order to
forecast the price of the winning bid in a given order and,
thus, adjust its bidding strategy. The paper presents our
agent, Mertacor, and focuses on the forecasting
mechanism it incorporates, aiming to optimal agent
efficiency.
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 Additional Information
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Citation:
Andreas L. Symeonidis, Vivia Nikolaidou, Pericles A. Mitkas,
"Exploiting Data Mining Techniques for Improving the Efficiency of a Supply Chain Management Agent,"
wi-iatw,
pp. 23-26,
2006 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops,
2006
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