English  |  正體中文  |  简体中文  |  Items with full text/Total items : 6491/11663
Visitors : 24728361      Online Users : 52
RC Version 3.2 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Adv. Search
Login ‧ Upload ‧ Help ‧ About ‧ Administer

Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/15879

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:[資訊管理學系所] 期刊論文

Files in This Item:

File SizeFormat
index.html0KbHTML454View/Open


All items in NCUEIR are protected by copyright, with all rights reserved.

 

DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback