A Multi-Agent system for documents classification
Rashid Ahmad, Safdar Ali, Do Hyeun Kim · 2012
Text classification is one of the important areas in data mining. Most of the Current text classification techniques concentrated on centralized/hierarchical approach. Due to the limited computing resources, these approaches could not classify large amount of data. The hierarchical approaches are also less robust and vulnerable due to system failure. We present a distributed documents classification technique using Multi-Agent technology. Naive Bays Classifier is used in a distributed environment for document classification. Experimental results show that the proposed technique is more robust, efficient and effective.