Communications of the ACM
Pattern recognition using neural networks: theory and algorithms for engineers and scientists
Pattern recognition using neural networks: theory and algorithms for engineers and scientists
A new and versatile method for association generation
Information Systems
Enterprise information systems: issues, challenges and viewpoints
Enterprise information systems
Data mining: concepts and techniques
Data mining: concepts and techniques
Devising Best Practices for Customization of a Multi-Agent Production Planning Technology
DEXA '02 Proceedings of the 13th International Workshop on Database and Expert Systems Applications
Agent Based Design and Simulation of Supply Chain Systems
WET-ICE '97 Proceedings of the 6th Workshop on Enabling Technologies on Infrastructure for Collaborative Enterprises
Designing And Managing The Supply Chain
Designing And Managing The Supply Chain
Data mining for agent reasoning: A synergy for training intelligent agents
Engineering Applications of Artificial Intelligence
Development of the Data Preprocessing Agent's Knowledge for Data Mining Using Rough Set Theory
RSKT '09 Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology
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As multi-agent systems and information agents obtain an increasing acceptance by application developers, existing legacy Enterprise Resource Planning (ERP) systems still provide the main source of data used in customer, supplier and inventory resource management. In this paper we present a multi-agent system, comprised of information agents, which cooperates with a legacy ERP in order to carry out orders posted by customers in an enterprise environment. Our system is enriched by the capability of producing recommendations to the interested customer through agent cooperation. At first, we address the problem of information workload in an enterprise environment and explore the opportunity of a plausible solution. Secondly we present the architecture of our system and the types of agents involved in it. Finally, we show how it manipulates retrieved information for efficient and facile customer-order management and illustrate results derived from real-data.