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Title: Discovery of Temporal Patterns from Process Instances
Authors: Hwang, San-Yih;Wei, Chih-Ping;Yang, Wan-Shiou
Contributors: 資訊管理學系
Keywords: Process mining;Knowledge discovery;Data mining;Temporal patterns;Association rules;Sequential patterns
Date: 2004-04
Issue Date: 2013-03-27T06:47:49Z
Publisher: Elsevier
Abstract: Existing work in process mining focuses on the discovery of the underlying process model from their instances. In this paper, we do not assume the existence of a single process model to which all process instances comply, and the goal is to discover a set of frequently occurring temporal patterns. Discovery of temporal patterns can be applied to various application domains to support crucial business decision-making. In this study, we formally defined the temporal pattern discovery problem, and developed and evaluated three different temporal pattern discovery algorithms, namely TP-Graph, TP-Itemset and TP-Sequence. Their relative performances are reported.
Relation: Computers in Industry, 53(3): 345-364
Appears in Collections:[Department of Information Management] Periodical Articles

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