dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Feelders, dr. A.J. | |
dc.contributor.author | Stekelenburg, D.J. | |
dc.date.accessioned | 2018-08-24T17:00:44Z | |
dc.date.available | 2018-08-24T17:00:44Z | |
dc.date.issued | 2018 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/30538 | |
dc.description.abstract | This work introduces the reader to a thesis study focusing on process mining. The goal of this thesis is to propose a method for describing semantical workflow patterns and to discover their occurrences in a given set of workflow models. Where many others study patterns solely on their syntax, we are interested in patterns with semantical value. This way, we capture patterns at a higher level and be able to reason about their behavior in a set of workflow models. Gaining insight into the usage
of workflow models helps workflow management systems to improve their engine. As a case study, we use data from the ERP-company AFAS Software BV. We show
that our proposed method is able to recognize a given pattern in such workflow data. | |
dc.description.sponsorship | Utrecht University | |
dc.format.extent | 723020 | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dc.title | Finding Semantical Patterns in Collections of Workflow Models | |
dc.type.content | Master Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | Workflow,workflow mining,word2vec,workflow pattern,semantics,process mining,AFAS Software | |
dc.subject.courseuu | Computing Science | |