Recommender Systems for Process Modeling Tools – A Literature Review

  • To construct a business process model manually is a highly complex and error-prone task which takes a lot of time and deep insights into the organizational structure, its operations and business rules. To improve the output of business analysts dealing with this process, different techniques have been introduced by researchers to support them during construction with helpful recommendations. These supporting recommendation systems vary in their way of what to recommend in the first place as well as their calculations taking place under the hood to recommend the most fitting element to the user. After a broad introduction into the field of business process modeling and its basic recommendation structures, this work will take a closer look at diverse proposals and descriptions published in current literature regarding implementationTo construct a business process model manually is a highly complex and error-prone task which takes a lot of time and deep insights into the organizational structure, its operations and business rules. To improve the output of business analysts dealing with this process, different techniques have been introduced by researchers to support them during construction with helpful recommendations. These supporting recommendation systems vary in their way of what to recommend in the first place as well as their calculations taking place under the hood to recommend the most fitting element to the user. After a broad introduction into the field of business process modeling and its basic recommendation structures, this work will take a closer look at diverse proposals and descriptions published in current literature regarding implementation strategies to effectively and efficiently assist modelers during their business process model creation. A critical analysis of presentations in the selected literature will point out strengths and weaknesses of their approaches, studies and descriptions of those. As a result, the final concept matrix in this work will give a precise and helpful overview about the key features and recommendation methods used and implemented in previous research studies to pinpoint an entry into future works without the downsides already spotted by fellow researchers.show moreshow less

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Metadaten
Author:Tim Weiskopf
URN:urn:nbn:de:kola-19759
Referee:Patrick Delfmann
Document Type:Master's Thesis
Language:English
Date of Publication (online):2019/10/21
Date of first Publication:2019/10/23
Publishing Institution:Universität Koblenz, Universitätsbibliothek
Granting Institution:Universität Koblenz, Fachbereich 4
Date of final exam:0019/04/29
Release Date:2019/10/23
Tag:Recommender Systems, Business Process Modeling, Literature Review
Page Number:V, 64
Institutes:Fachbereich 4 / Institut für Wirtschafts- und Verwaltungsinformatik
Licence (German):Es gilt das deutsche Urheberrecht: § 53 UrhG
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