Sequence Alignment Adaptation for Process Diagnostics and Delta Analysis

Date

2013-09-13

Author

Esgin, Eren
Karagöz, Pınar

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Business process management (BPM) paradigm gains growing attention by providing generic process design and execution capabilities. During execution, many business processes leave casual footprints (event logs) at these transactional information systems. Process mining aims to extract business processes by distilling event logs for knowledge. Sequence alignment is a technique that is frequently used in domains including bioinformatics, language/text processing and finance. It aims to arrange structures, such as protein sequences to identify similar regions. In this study, we focus on a hybrid quantitative approach for performing process diagnostics, i.e. comparing the similarity among process models based on the established dominant behavior concept and Needleman-Wunsch algorithm.

Subject Keywords

Process Mining, Sequence alignment, Process diagnostics, Dominant behavior, Needleman-Wunsch algorithm

URI

https://hdl.handle.net/11511/53177

Collections

Department of Computer Engineering, Conference / Seminar