A Customizable Multi-Agent System for Distributed Data Mining

We present a general Multi-Agent System framework for distributed data mining based on a Peer-toPeer model. The framework adopts message-based asynchronous communication and a dynamic load balancing policy that is particularly suitable for irregular search algorithms. A modular design allows a separation of the general-purpose system protocols and software components from the specific data mining algorithm. While the general architecture has been implemented and successfully tested on a parallel frequent subgraph mining algorithm, several interesting issues still have to be explored. The present work will discuss them and will introduce the ongoing research efforts aimed at exploiting and leveraging the MAS for distributed data mining applications. 1 P2P-BASED MAS for Distributed Data Mining The last decade has seen an ever increasing availability of large amounts of data in many fields of science and in many IT applications. Data mining techniques have become popular techniques, whic...

• Type: Conference
• Year: 2006
• Where: EUMAS
• Authors: Giancarlo Fortino, Giuseppe Di Fatta
• Keywords: Data Mining, Data Mining Algorithm, EUMAS 2006, Intelligent Agents, Mining Algorithm