Towards the Automated Annotation of Process Models

H. Leopold, C. Meilicke, M. Fellmann, F. Pittke, H. Stuckenschmidt, J. Mendling

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


Many techniques for the advanced analysis of process models build on the annotation of process models with elements from predefined vocabularies such as taxonomies. However, the manual annotation of process models is cumbersome and sometimes even hardly manageable taking the size of taxonomies into account. In this paper, we present the first approach for automatically annotating process models with the concepts of a taxonomy. Our approach builds on the corpus-based method of second-order similarity, different similarity functions, and a Markov Logic formalization. An evaluation with a set of 12 process models consisting of 148 activities and the PCF taxonomy consisting of 1,131 concepts demonstrates that our approach produces satisfying results.
Original languageEnglish
Title of host publicationProceeding of the 27th International Conference on Advanced Information Systems Engineering (CAiSE 2015)
ISBN (Print)978-3-319-19068-6
Publication statusPublished - 2016

Publication series

NameLecture Notes in Computer Science


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