TY - JFULL AU - H. Baazaoui Zghal and S. Faiz and H. Ben Ghezala PY - 2007/6/ TI - A Framework for Data Mining Based Multi-Agent: An Application to Spatial Data T2 - International Journal of Computer and Information Engineering SP - 1409 EP - 1414 VL - 1 SN - 1307-6892 UR - https://publications.waset.org/pdf/6120 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 5, 2007 N2 - Data mining is an extraordinarily demanding field referring to extraction of implicit knowledge and relationships, which are not explicitly stored in databases. A wide variety of methods of data mining have been introduced (classification, characterization, generalization...). Each one of these methods includes more than algorithm. A system of data mining implies different user categories,, which mean that the user-s behavior must be a component of the system. The problem at this level is to know which algorithm of which method to employ for an exploratory end, which one for a decisional end, and how can they collaborate and communicate. Agent paradigm presents a new way of conception and realizing of data mining system. The purpose is to combine different algorithms of data mining to prepare elements for decision-makers, benefiting from the possibilities offered by the multi-agent systems. In this paper the agent framework for data mining is introduced, and its overall architecture and functionality are presented. The validation is made on spatial data. Principal results will be presented. ER -