Significant correlation pattern mining in smart homes

NCUIR > School of Management at National Central University > Department of Information Management > journal & Dissertation > Item 987654321/107032

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/107032

Title:	Significant correlation pattern mining in smart homes
Authors:	陳以錚;Chen, Yi-Cheng;Peng, Wen-Chih;Huang, Jiun-Long;Lee, Wang-Chien
Contributors:	管理學院資訊管理學系
Date:	2015-04-01
Issue Date:	2026-04-23 13:53:49 (UTC+8)
Publisher:	Association for Computing Machinery (ACM)
Abstract:	摘要： Owing to the great advent of sensor technology, the usage data of appliances in a house can be logged and collected easily today. However, it is a challenge for the residents to visualize how these appliances are used. Thus, mining algorithms are much needed to discover appliance usage patterns. Most previous studies on usage pattern discovery are mainly focused on analyzing the patterns of single appliance rather than mining the usage correlation among appliances. In this article, a novel algorithm, namely Correlation Pattern Miner (CoPMiner), is developed to capture the usage patterns and correlations among appliances probabilistically. CoPMiner also employs four pruning techniques and a statistical model to reduce the search space and filter out insignificant patterns, respectively. Furthermore, the proposed algorithm is applied on a real-world dataset to show the practicability of correlation pattern mining. 出版日期： 2015-05-20 出處： ACM transactions on intelligent systems and technology, 2015-05, Vol.6 (3), p.1-23 資源來源： ACM Digital Library Complete 識別號： ISSN: 2157-6904 識別號： EISSN: 2157-6912 識別號： DOI: 10.1145/2700484
Appears in Collections:	[Department of Information Management] journal & Dissertation

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