Publication Details

Use of Frequent Itemset Mining Techniques to Analyze Business Processes

BARTÍK, V.; POSPÍŠIL, M. 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. Lisbon: SciTePress - Science and Technology Publications, 2015. p. 273-280. ISBN: 978-989-758-158-8.
Czech title
Využití frekventovaných množin pro analýzu obchodních procesů
Type
conference paper
Language
English
Authors
Bartík Vladimír, Ing., Ph.D. (DIFS)
Pospíšil Milan, Ing.
Keywords

Business Process, Process Mining, Frequent Itemsets, Simulator of Production
History, Association Rules.

Abstract

Analysis of business process data can be used to discover reasons of delays and
other problems of 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.

Published
2015
Pages
273–280
Proceedings
Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management
Conference
7th International Conference on Knowledge Discovery and Information Retrieval, Lisbon, PT
ISBN
978-989-758-158-8
Publisher
SciTePress - Science and Technology Publications
Place
Lisbon
UT WoS
000411797400029
EID Scopus
BibTeX
@inproceedings{BUT119870,
  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",
  year="2015",
  pages="273--280",
  publisher="SciTePress - Science and Technology Publications",
  address="Lisbon",
  isbn="978-989-758-158-8"
}
Back to top