Retrieval and clustering for supporting business process adjustment and analysis

  • Authors:
  • Stefania Montani;Giorgio Leonardi

  • Affiliations:
  • DISIT, Institute of Computer Science, Universití del Piemonte Orientale, Viale Michel 11, I-15121 Alessandria, Italy;DISIT, Institute of Computer Science, Universití del Piemonte Orientale, Viale Michel 11, I-15121 Alessandria, Italy

  • Venue:
  • Information Systems
  • Year:
  • 2014

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Abstract

In this paper, we describe a framework able to support run-time adjustment and a posteriori analysis of business processes, which exploits the retrieval step of the Case-based Reasoning (CBR) methodology. In particular, our framework allows to retrieve traces of process execution similar to the current one. Moreover, it supports an automatic organization of the trace database content through the application of hierarchical clustering techniques. Results can provide help both to end users, in the process execution phase, and to process engineers, in (formal) process conformance evaluation and long term process schema redesign. Retrieval and clustering rely on a distance definition able to take into account temporal information in traces. This metric has outperformed simpler distance definitions in our experiments, which were conducted in a real-world application domain.