Semantic analysis of business process executions

Fabio Casati, Ming Chien Shan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

29 Citations (Scopus)

Abstract

Business Process Management Systems log a large amount of operational data about processes and about the (human and automated) resources involved in their executions. This information can be analyzed for assessing the quality of business operations, identify problems, and suggest solutions. However, current process analysis systems lack the functionalities required to provide information that can be immediately digested and used by business analysts to take decisions. In this paper we discuss the limitations of existing approaches and we present a system and a set of techniques, developed at Hewlett-Packard, that overcome this limitations, enabling the use of log data for efficient business-level analysis of business processes.

Original languageEnglish
Title of host publicationAdvances in Database Technology, EDBT 2002 - 8th International Conference on Extending Database Technology, Proceedings
Pages287-296
Number of pages10
Volume2287 LNCS
Publication statusPublished - 2002
Externally publishedYes
Event8th International Conference on Extending Database Technology, EDBT 2002 - Prague, Czech Republic
Duration: 25 Mar 200227 Mar 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2287 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Extending Database Technology, EDBT 2002
CountryCzech Republic
CityPrague
Period25.3.0227.3.02

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Casati, F., & Shan, M. C. (2002). Semantic analysis of business process executions. In Advances in Database Technology, EDBT 2002 - 8th International Conference on Extending Database Technology, Proceedings (Vol. 2287 LNCS, pp. 287-296). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2287 LNCS).