Context-Sensitive Textual Recommendations for Incomplete Process Model Elements

Many organizations manage repositories of several thousand process models. It has been observed that a lot of these models have quality issues. For the model collections we have worked with, we found that every third model contains elements with incomplete element names. While prior research has pro...

Full description

Saved in:
Bibliographic Details
Published inBusiness Process Management Vol. 9253; pp. 189 - 197
Main Authors Pittke, Fabian, Richetti, Pedro H. Piccoli, Mendling, Jan, Baião, Fernanda Araujo
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2015
Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Many organizations manage repositories of several thousand process models. It has been observed that a lot of these models have quality issues. For the model collections we have worked with, we found that every third model contains elements with incomplete element names. While prior research has proposed techniques to close gaps on the structural level, approaches that address the naming of incompletely specified model elements are missing. In this paper, we propose three strategies for naming process elements and a context-sensitive ranking to present the most relevant naming recommendations to the user. We prototypically implemented our approach and conducted an extensive user experiment with real-world process models in order to assess the usefulness of the recommendations. The results show that our approach fulfills its purpose and creates meaningful recommendations.
ISBN:9783319230627
331923062X
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-23063-4_13