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Domain modelling of server monitoring system using MCRDR

Citation

Foo, WM and Fan, B and Kang, BH, Domain modelling of server monitoring system using MCRDR, AISAT 2009 The 3rd International Workshop on Artificial Intelligence in Science and Technology, 23-24 November 2009, Hobart Tasmania EJ ISBN 978-1-86295-550-9 (2009) [Refereed Conference Paper]


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Copyright Statement

Copyright 2009 University of Tasmania

Official URL: http://www.eng.utas.edu.au/conferences/AISAT/aisat...

Abstract

Domain Modelling is a pre-process to classify the raw data into a modeled data for human or expert to make a further process. Unfortunately, domain modelling scheme might be changeable due to the environment change and expert experience. Server monitoring system is an example and used for the experiment. Server monitoring system is operated in varied environment and re-quire different domain modelling scheme for each environment. This thesis re-search is to explore the applicability of the MCRDR technique of knowledge acquisition toward the server monitoring system domain modelling based on the time series performance metric from agents to provided modelled data. MCRDR is an incrementally knowledge acquisition method to acquire only correct knowledge from the expert and administrator. Though this experimentation, it is improved the accuracy and reliability on the modelled data for human or expert to make a further process.

Item Details

Item Type:Refereed Conference Paper
Keywords:Domain Modelling, Server Monitoring System, MCRDR, Inference
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Artificial Intelligence and Image Processing not elsewhere classified
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Application Tools and System Utilities
Author:Fan, B (Mr Boyi Fan)
Author:Kang, BH (Professor Byeong Kang)
ID Code:62144
Year Published:2009
Deposited By:Computing and Information Systems
Deposited On:2010-03-10
Last Modified:2014-12-09
Downloads:0

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