Process mining, discovery, and integration using distance measures Conference Paper uri icon

abstract

  • Business processes continue to play an important role in today's service-oriented enterprise computing systems. Mining, discovering, and integrating processoriented services has attracted growing attention in the recent year. In this paper we present a quantitative approach to modeling and capturing the similarity and dissimilarity between different process designs. We derive the similarity measures by analyzing the process dependency graphs of the participating workflow processes. We first convert each process dependency graph into a normalized process matrix. Then we calculate the metric space distance between the normalized matrices. This distance measure can be used as a quantitative and qualitative tool in process mining, process merging, and process clustering, and ultimately it can reduce or minimize the costs involved in design, analysis, and evolution of workflow systems. 2006 IEEE.

name of conference

  • 2006 IEEE International Conference on Web Services (ICWS'06)

published proceedings

  • ICWS 2006: IEEE International Conference on Web Services, Proceedings

author list (cited authors)

  • Bae, J., Liu, L., Caverlee, J., & Rouse, W. B.

citation count

  • 38

complete list of authors

  • Bae, Joonsoo||Liu, Ling||Caverlee, James||Rouse, William B

publication date

  • September 2006