Intelligent service reasoning model using data mining

Authors:
Myungseok Kang;Changyu Kim;Inhwa Hong;Jeongjin Kang
Affiliations:
Korea Electronics Technology Institute, Seongnam-si, Gyeonggi-do, Korea;Korea Electronics Technology Institute, Seongnam-si, Gyeonggi-do, Korea;Korea Electronics Technology Institute, Seongnam-si, Gyeonggi-do, Korea;Dong Seoul College, Seongnam-si, Gyeonggi-do, Korea
Venue:
Proceedings of the 2009 International Conference on Hybrid Information Technology
Year:
2009

Citing 2
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C4.5: programs for machine learning

C4.5: programs for machine learning
Database Mining: A Performance Perspective

IEEE Transactions on Knowledge and Data Engineering

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Abstract

This paper proposes an Intelligent Service Reasoning (ISR) model using data mining in smart home environments. This model creates a service tree used for service reasoning on the basis of the C4.5 algorithm, one of decision tree algorithms, and determines the services that will be provided to users through a quantitative weight estimation algorithm that uses a quantitative characteristic rule and a quantitative discrimination rule. The effectiveness in the performance of the developed model is validated through a smart home-network simulation.