Mining Temporal Patterns in Time Interval-Based Data

NCUIR > School of Management at National Central University > Department of Information Management > journal & Dissertation > Item 987654321/106868

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/106868

Title:	Mining Temporal Patterns in Time Interval-Based Data
Authors:	陳以錚;Chen, Yi-Cheng;Peng, Wen-Chih;Lee, Suh-Yin
Contributors:	管理學院資訊管理學系
Keywords:	Algorithm design and analysis;Data mining;Distribution functions;Home appliances;interval-based event;Pattern recognition;Probabilistic logic;representation;Sequential analysis;sequential pattern;temporal pattern
Date:	2015-12-01
Issue Date:	2026-04-23 13:47:06 (UTC+8)
Publisher:	IEEE Computer Society;IEEE
Abstract:	摘要： Sequential pattern mining is an important subfield in data mining. Recently, applications using time interval-based event data have attracted considerable efforts in discovering patterns from events that persist for some duration. Since the relationship between two intervals is intrinsically complex, how to effectively and efficiently mine interval-based sequences is a challenging issue. In this paper, two novel representations, endpoint representation and endtime representation, are proposed to simplify the processing of complex relationships among event intervals. Based on the proposed representations, three types of interval-based patterns: temporal pattern, occurrence-probabilistic temporal pattern, and duration-probabilistic temporal pattern, are defined. In addition, we develop two novel algorithms, Temporal Pattern Miner (TPMiner) and Probabilistic Temporal Pattern Miner (P-TPMiner), to discover three types of interval-based sequential patterns. We also propose three pruning techniques to further reduce the search space of the mining process. Experimental studies show that both algorithms are able to find three types of patterns efficiently. Furthermore, we apply proposed algorithms to real datasets to demonstrate the effectiveness and validate the practicability of proposed patterns. 其他題名： TKDE 出版者： IEEE 出版日期： 2015-12-01 出處： IEEE transactions on knowledge and data engineering, 2015-12, Vol.27 (12), p.3318-3331 資源來源： IEEE Electronic Library (IEL) 識別號： ISSN: 1041-4347 識別號： DOI: 10.1109/TKDE.2015.2454515 識別號： CODEN: ITKEEH
Appears in Collections:	[Department of Information Management] journal & Dissertation

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