Title :
A Multi-Agent system for documents classification
Author :
Ahmad, Rabiah ; Ali, Shady ; Kim, D.H.
Author_Institution :
Dept. of Comput. Eng., Jeju Nat. Univ., Jeju, South Korea
Abstract :
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.
Keywords :
data mining; multi-agent systems; pattern classification; text analysis; centralized classification approach; data mining; document classification; hierarchical classification approach; multi-agent system; naive Bayes classifier; text classification; Accuracy; Artificial intelligence; Computers; Multi-agent systems; Niobium; Text categorization; classification; multi-agent system; naïve bayes; text mining;
Conference_Titel :
Open Source Systems and Technologies (ICOSST), 2012 International Conference on
Conference_Location :
Lahore
Print_ISBN :
978-1-4673-3094-7
DOI :
10.1109/ICOSST.2012.6472823