Improving Parallel Pattern Discovery from Directly Follows Graph Model

Indra Waspada, Riyanarto Sarno, Endang Siti Astuti, Hanung Nindito Prasetyo, Raden Budirahario

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Process model discovery is an important part of process mining. State-of-The-Art algorithms still have trouble detecting long parallel patterns with incomplete concurrency patterns. This paper proposes a method to exploit the characteristics of parallel block patterns to discover an accurate parallel block. The experiment compared the proposed method with state-of-The-Art algorithms, Inductive Miner and Split Miner. The quality of the discovery results is measured using fitness, precision, and f-score. The experimental results show that the proposed method outperforms the state-of-The-Art algorithm in discovering long parallel block patterns with incomplete concurrency patterns.

Original languageEnglish
Title of host publication2022 5th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages769-774
Number of pages6
ISBN (Electronic)9781665455121
DOIs
Publication statusPublished - 2022
Event5th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2022 - Virtual, Online, Indonesia
Duration: 8 Dec 20229 Dec 2022

Publication series

Name2022 5th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2022

Conference

Conference5th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2022
Country/TerritoryIndonesia
CityVirtual, Online
Period8/12/229/12/22

Keywords

  • concurrency pattern
  • directly follows graph
  • parallel pattern
  • process mining
  • process model discovery

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