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Process-Specific Extensions for Enhanced Recommender Systems in Business Process Management

Title data

Petter, Sebastian ; Jablonski, Stefan:
Process-Specific Extensions for Enhanced Recommender Systems in Business Process Management.
In: Almeida, João Paulo A. ; Di Ciccio, Claudio ; Kalloniatis, Christos (ed.): Advanced Information Systems Engineering Workshops. - Cham : Springer , 2024 . - pp. 275-290
ISBN 978-3-031-61003-5
DOI: https://doi.org/10.1007/978-3-031-61003-5_24

Abstract in another language

In Business Process Management (BPM) the integration of advanced recommender systems emerges as a critical strategy to enhance process efficiency and user satisfaction. Despite the dissemination of these systems, there remains a distinct lack of incorporating execution relevant context data, particularly those generated during process execution and prevailing environmental conditions. This paper addresses this gap by proposing process-specific extensions for augmenting an existing recommender system framework. Our approach not only enhances the adaptability and accuracy of recommendations but also sustains the applicability of existing algorithms, ensuring seamless integration into available recommender frameworks. The potential of this refined approach is demonstrated by evaluating a process scenario based on synthetic data.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: Business process management; Recommender systems; User-centered process improvement
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science IV
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science IV > Chair Applied Computer Science IV - Univ.-Prof. Dr.-Ing. Stefan Jablonski
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 11 Jun 2024 08:19
Last Modified: 11 Jun 2024 08:19
URI: https://eref.uni-bayreuth.de/id/eprint/89722