Quotation Kala, Taavi, Maggi, Fabrizio Maria, Di Ciccio, Claudio, Di Francescomarino, Chiara. 2016. Apriori and Sequence Analysis for Discovering Declarative Process Models. In 20th IEEE International Enterprise Distributed Object Computing Conference, EDOC 2016, Vienna, Austria, September 5-9, 2016, Hrsg. Florian Matthes, Jan Mendling, Stefanie Rinderle-Ma, 1-9. Vienna, Austria: IEEE.


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Abstract

The aim of process discovery is to build a process model from an event log without prior information about the process. The discovery of declarative process models is useful when a process works in an unpredictable and unstable environment since several allowed paths can be represented as a compact set of rules. One of the tools available in the literature for discovering declarative models from logs is the Declare Miner, a plug-in of the process mining tool ProM. Using this plug-in, the discovered models are represented using Declare, a declarative process modelling language based on LTL for finite traces. In this paper, we use a combination of an Apriori algorithm and a group of algorithms for Sequence Analysis to improve the performances of the Declare Miner. Using synthetic and real life event logs, we show that the new implemented core of the plug-in allows for a significant performance improvement.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Contribution to conference proceedings
Language English
Title Apriori and Sequence Analysis for Discovering Declarative Process Models
Title of whole publication 20th IEEE International Enterprise Distributed Object Computing Conference, EDOC 2016, Vienna, Austria, September 5-9, 2016
Editor Florian Matthes, Jan Mendling, Stefanie Rinderle-Ma
Page from 1
Page to 9
Location Vienna, Austria
Publisher IEEE
Year 2016
URL http://dx.doi.org/10.1109/EDOC.2016.7579378

Associations

People
Di Ciccio, Claudio (Former researcher)
External
Di Francescomarino, Chiara (Fondazione Bruno Kessler, Italy)
Kala, Taavi (University of Tartu, Estonia)
Maggi, Fabrizio Maria (University of Tartu, Estonia)
Organization
Applied Information Technology with Focus on IT in Organization (Details)
Research areas (Ă–STAT Classification 'Statistik Austria')
1105 Computer software (Details)
1108 Informatics (Details)
1109 Information and data processing (Details)
1127 Information science (Details)
5367 Management information systems (Details)
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