An Intelligent System for Mining and Maintaining Correlation Patterns among Appliances in Smart Home

淡江大學機構典藏 > 工學院 > 資訊工程學系暨研究所 > 會議論文 > Item 987654321/98681

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题名:	An Intelligent System for Mining and Maintaining Correlation Patterns among Appliances in Smart Home
作者:	Yi-Cheng Chen;Julia Tzu-Ya Weng
贡献者:	資訊工程學系暨研究所
关键词:	sensor data analysis smart home correlation pattern intelligent system incremental mining
日期:	2014-08-26
上传时间:	2014-09-10 01:56:38 (UTC+8)
摘要:	Recently, due to the great advent of sensor technology, residents can collect the usage data of appliances in a house easily. However, with data progressively generating, it is still a challenge to visualize how these appliances are used. Thus, a mining and maintaining system is needed to incrementally discover appliance usage patterns. Most previous studies on usage pattern discovery are mainly focused on analyzing the patterns of single appliance and do not consider the incremental maintenance of mining results. In this paper, a novel system, namely, Dynamic Correlation Mining System (DCMS) is developed to capture and maintain the correlation patterns among appliances incrementally. The experimental results indicate that proposed system is efficient in execution time and possesses scalability. Furthermore, we apply DCMS on a real-world dataset to show the practicability.
關聯:	The 10-th Workshop on Wireless, Ad Hoc and Sensor Networks (WASN 2014)
显示于类别:	[資訊工程學系暨研究所] 會議論文

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