Abstract
Deployment flexibility, low development cost, and value-adding tools are some of the features that developers are looking for in ERP systems. Modularization through software agents is one way of achieving these objectives. In this sense, the present paper proposes the planning, implementation and integration of a software agent for association rule mining into an ERP system. The development and use of tools for all Knowledge Discovery in Databases (KDD) phases (pre-processing, data mining and post-processing), will be presented. This includes input data, file loading for the agent processing, use of the Apriori association rule mining algorithm, generation of output files with association rules, use of agent outputs for database storage and use of the stored data by the item recommendation tool. Experiments were carried out focusing the assessment of the running profile for databases of different sizes and using different computational architectures.