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Authors: Vladimír Bartík and Milan Pospíšil

Affiliation: Brno University of Technology and Faculty of Information Technology, Czech Republic

Keyword(s): Business Process, Process Mining, Frequent Itemsets, Simulator of Production History, Association Rules.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Analytics ; Data Analytics ; Data Engineering ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Process Mining ; Symbolic Systems

Abstract: Analysis of business process data can be used to discover reasons of delays and other problems in a business process. This paper presents an approach, which uses a simulator of production history. This simulator allows detecting problems at various production machines, e.g. extremely long queues of products waiting before a machine. After detection, data about products processed before the queue increased are collected. Frequent itemsets obtained from this dataset can be used to describe the problem and reasons of it. The whole process of frequent itemset mining will be described in this paper. It is also focused on description of several necessary modifications of basic methods usually used to discover frequent itemsets.

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Paper citation in several formats:
Bartík, V. and Pospíšil, M. (2015). Use of Frequent Itemset Mining Techniques to Analyze Business Processes. In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - KDIR; ISBN 978-989-758-158-8; ISSN 2184-3228, SciTePress, pages 273-280. DOI: 10.5220/0005598102730280

@conference{kdir15,
author={Vladimír Bartík. and Milan Pospíšil.},
title={Use of Frequent Itemset Mining Techniques to Analyze Business Processes},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - KDIR},
year={2015},
pages={273-280},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005598102730280},
isbn={978-989-758-158-8},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - KDIR
TI - Use of Frequent Itemset Mining Techniques to Analyze Business Processes
SN - 978-989-758-158-8
IS - 2184-3228
AU - Bartík, V.
AU - Pospíšil, M.
PY - 2015
SP - 273
EP - 280
DO - 10.5220/0005598102730280
PB - SciTePress

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