Data transformation and semantic log purging for process mining

Linh Thao Ly, Conrad Indiono, Jürgen Mangler, Stefanie Rinderle-Ma

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

35 Scopus citations

Abstract

Existing process mining approaches are able to tolerate a certain degree of noise in the process log. However, processes that contain infrequent paths, multiple (nested) parallel branches, or have been changed in an ad-hoc manner, still pose major challenges. For such cases, process mining typically returns spaghetti-models, that are hardly usable even as a starting point for process (re-)design. In this paper, we address these challenges by introducing data transformation and pre-processing steps that improve and ensure the quality of mined models for existing process mining approaches. We propose the concept of semantic log purging, the cleaning of logs based on domain specific constraints utilizing semantic knowledge which typically complements processes. Furthermore we demonstrate the feasibility and effectiveness of the approach based on a case study in the higher education domain. We think that semantic log purging will enable process mining to yield better results, thus giving process (re-)designers a valuable tool.

Original languageEnglish
Title of host publicationAdvanced Information Systems Engineering - 24th International Conference, CAiSE 2012, Proceedings
Pages238-253
Number of pages16
DOIs
StatePublished - 2012
Externally publishedYes
Event24th International Conference on Advanced Information Systems Engineering, CAiSE 2012 - Gdansk, Poland
Duration: 25 Jun 201229 Jun 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7328 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference24th International Conference on Advanced Information Systems Engineering, CAiSE 2012
Country/TerritoryPoland
CityGdansk
Period25/06/1229/06/12

Keywords

  • Data transformation
  • Log purging
  • Process constraints
  • Process mining

Fingerprint

Dive into the research topics of 'Data transformation and semantic log purging for process mining'. Together they form a unique fingerprint.

Cite this