Abstract

An intentional process model is known to analyze processes deeply and provide recommendations for the upcoming processes. Nevertheless, the discovery of intentions is a difficult task because the intentions are not recorded in the event log, but they encourage the executable activities in the event log. Map Miner is the latest algorithm to depict the intentional process model. A disadvantage of this algorithm is the inability to determine strategies that contain same activities with the different sequence with other strategies. This disadvantage leads failure on the intentional process model. This research proposes an algorithm for discovering an intentional process model by considering the sequence of activities and CHMM (Coupled Hidden Markov Model). The probabilities and states of CHMM are utilized for the formation of the intentional process model. The experiment shows that the proposed algorithm with considering the sequence of activities gets an appropriate intentional process model. It also demonstrates that an obtained intentional process model using proposed algorithm gets the better validity than an intentional process model using Map Miner Method.

Original languageEnglish
Title of host publicationProceedings - 2017 4th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2017
EditorsHatib Rahmawan, Mochammad Facta, Munawar A. Riyadi, Deris Stiawan
PublisherInstitute of Advanced Engineering and Science
ISBN (Electronic)9781538605486
DOIs
Publication statusPublished - 22 Dec 2017
Event4th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2017 - Yogyakarta, Indonesia
Duration: 19 Sept 201721 Sept 2017

Publication series

NameInternational Conference on Electrical Engineering, Computer Science and Informatics (EECSI)
Volume2017-December
ISSN (Print)2407-439X

Conference

Conference4th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2017
Country/TerritoryIndonesia
CityYogyakarta
Period19/09/1721/09/17

Keywords

  • Coupled hidden markov model
  • Event log
  • Intention mining
  • Process model
  • Validity

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