intelligent service reasoning model using data mining
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.
data mining intelligent service reasoning (isr) smart environments