An Efficient Method for Mining Event-Related Potential Patterns
In the present paper, we propose a Neuroelectromagnetic Ontology Framework (NOF) for mining Event-related Potentials (ERP) patterns as well as the process. The aim for this research is to develop an infrastructure for mining, analysis and sharing the ERP domain ontologies. The outcome of this research is a Neuroelectromagnetic knowledge-based system. The framework has 5 stages: 1) Data pre-processing and preparation; 2) Data mining application; 3) Rule Comparison and Evaluation; 4) Association rules Post-processing 5) Domain Ontologies. In 5th stage a new set of hidden rules can be discovered base on comparing association rules by domain ontologies and expert rules.
Keywords: EEG, MEG, Event-related Potentials (ERP), Data Mining, ontology
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ABOUT THE AUTHORS
Seyed Aliakbar Mousavi
Seyed Aliakbar Mousavi Aslarzanagh is a researcher in University Science Malaysia, School of Computer Science. He obtained E-commerce Bachelor degree from Multimedia University in 2010 and continued his study to a research degree in Computer Science. He is currently cooperating with Department of Neuroscience in USM Kubang Kerian and multimedia research group in an interdisciplinary fields of Neuroinformatic and Data Mining Knowledge discovery.
Muhammad Rafie Hj Arshad
Assoc Prof Muhammad Rafie Hj. Mohd. Arshad achieved his Bachelor degree from Macalester College, Minnesota, U.S.A. and his MBA-MIS from Dallas, Texas, U.S.A.
Hasimah Hj Mohamed
Hasimah Hj Mohamed has obtained her bachelor degree from Universiti Teknology Malaysia and her MSc from Universiti Sains Malaysia. Currently she is a senior lecturer at Universiti Sains Malaysia, and also a PhD candidate at National University of Malaysia.
Saleh Ali Alomari
Saleh Ali K. Al-Omari has obtained his Bachelor degree in Computer Science from Jerash University, Jordan in 2004-2005 and Master degree in Computer Science from Universiti Sains Malaysia, Penang, Malaysia in 2007. Currently, He is a PhD candidate at the School of Computer Science, Universiti Sains Malaysia. He is the candidate of the Multimedia Computing Research Group, School of Computer Science, USM. He is a member and reviewer of several international journals and conferences (IEICE, JDCTA, IEEE, IACSIT, AIRCC, etc). His main research area interest are in includes Peer to Peer Media Streaming, Video on Demand over Ad Hoc Networks, MANETs, and Multimedia Networking, Mobility.
Seyed Aliakbar Mousavi
Seyed Aliakbar Mousavi Aslarzanagh is a researcher in University Science Malaysia, School of Computer Science. He obtained E-commerce Bachelor degree from Multimedia University in 2010 and continued his study to a research degree in Computer Science. He is currently cooperating with Department of Neuroscience in USM Kubang Kerian and multimedia research group in an interdisciplinary fields of Neuroinformatic and Data Mining Knowledge discovery.
Muhammad Rafie Hj Arshad
Assoc Prof Muhammad Rafie Hj. Mohd. Arshad achieved his Bachelor degree from Macalester College, Minnesota, U.S.A. and his MBA-MIS from Dallas, Texas, U.S.A.
Hasimah Hj Mohamed
Hasimah Hj Mohamed has obtained her bachelor degree from Universiti Teknology Malaysia and her MSc from Universiti Sains Malaysia. Currently she is a senior lecturer at Universiti Sains Malaysia, and also a PhD candidate at National University of Malaysia.
Saleh Ali Alomari
Saleh Ali K. Al-Omari has obtained his Bachelor degree in Computer Science from Jerash University, Jordan in 2004-2005 and Master degree in Computer Science from Universiti Sains Malaysia, Penang, Malaysia in 2007. Currently, He is a PhD candidate at the School of Computer Science, Universiti Sains Malaysia. He is the candidate of the Multimedia Computing Research Group, School of Computer Science, USM. He is a member and reviewer of several international journals and conferences (IEICE, JDCTA, IEEE, IACSIT, AIRCC, etc). His main research area interest are in includes Peer to Peer Media Streaming, Video on Demand over Ad Hoc Networks, MANETs, and Multimedia Networking, Mobility.