On the discovery of process models from their instances

San Yih Hwang, Wan Shiou Yang

Research output: Contribution to journalArticlepeer-review

44 Citations (Scopus)


A thorough understanding of the way in which existing business processes currently practice is essential from the perspectives of both process reengineering and workflow management. In this paper, we present a framework and algorithms that derive the underlying process model from past executions. The process model employs a directed graph for representing the control dependencies among activities and associates a Boolean function on each edge to indicate the condition under which the edge is to be enabled. By modeling the execution of an activity as an interval, we have developed an algorithm that derives the directed graph in a faster, more accurate manner. This algorithm is further enhanced with a noise handling mechanism to tolerate noise, which frequently occur in the real world. Experimental results show that the proposed algorithm outperforms the existing ones in terms of efficiency and quality.

Original languageEnglish
Pages (from-to)41-57
Number of pages17
JournalDecision Support Systems
Issue number1
Publication statusPublished - 2002 Dec 1

All Science Journal Classification (ASJC) codes

  • Management Information Systems
  • Information Systems
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • Information Systems and Management

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