Publications
2026
Grewenig, Lisa; Zeyen, Christian; Schultheis, Alexander; Malburg, Lukas; Bergmann, Ralph
Challenges and Support Potentials in the Development of CBR Applications Proceedings Article
In: Case-Based Reasoning Research and Development - 34th International Conference, ICCBR 2026, Bremen, Germany, August 13 - 16, 2026, Proceedings, Springer, 2026, (Accepted for Publication.).
Abstract | BibTeX | Tags: Case-Based Reasoning, CBR Applications, Development Support, Domain Experts, Knowledge Engineering
@inproceedings{GrewenigZSMB2026,
title = {Challenges and Support Potentials in the Development of CBR Applications},
author = {Lisa Grewenig and Christian Zeyen and Alexander Schultheis and Lukas Malburg and Ralph Bergmann},
year = {2026},
date = {2026-01-01},
booktitle = {Case-Based Reasoning Research and Development - 34th International Conference, ICCBR 2026, Bremen, Germany, August 13 - 16, 2026, Proceedings},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
abstract = {Developing Case-Based Reasoning applications is a knowledge-intensive task that consists of numerous demanding and time-consuming development steps. Major challenges are posed by knowledge engineering since CBR systems depend on capturing, validating, and maintaining domain knowledge in an explicit, machine-interpretable form. This usually can be done only in a close interdisciplinary collaboration between CBR and domain experts. To support development, previous works put forth a broad spectrum of support functions but mostly have not yet addressed the synergies of support functions or the potentials for involving domain experts, particularly those without knowledge-engineering experience. To further improve the accessibility of CBR frameworks and to reduce the effort of development, this paper consolidates development challenges along with corresponding support methods. In addition, we address the potentials for involving domain experts in the development with the help of support functions. We derived development challenges and support potentials from literature and conducted an explorative survey in the CBR research community.},
note = {Accepted for Publication.},
keywords = {Case-Based Reasoning, CBR Applications, Development Support, Domain Experts, Knowledge Engineering},
pubstate = {published},
tppubtype = {inproceedings}
}
Developing Case-Based Reasoning applications is a knowledge-intensive task that consists of numerous demanding and time-consuming development steps. Major challenges are posed by knowledge engineering since CBR systems depend on capturing, validating, and maintaining domain knowledge in an explicit, machine-interpretable form. This usually can be done only in a close interdisciplinary collaboration between CBR and domain experts. To support development, previous works put forth a broad spectrum of support functions but mostly have not yet addressed the synergies of support functions or the potentials for involving domain experts, particularly those without knowledge-engineering experience. To further improve the accessibility of CBR frameworks and to reduce the effort of development, this paper consolidates development challenges along with corresponding support methods. In addition, we address the potentials for involving domain experts in the development with the help of support functions. We derived development challenges and support potentials from literature and conducted an explorative survey in the CBR research community.
2023
Schultheis, Alexander; Zeyen, Christian; Bergmann, Ralph
An Overview and Comparison of Case-Based Reasoning Frameworks Proceedings Article
In: Case-Based Reasoning Research and Development - 31st International Conference, ICCBR 2023, Aberdeen, Scotland, July 17-20, 2023, Proceedings, pp. 327–343, Springer, 2023.
Abstract | Links | BibTeX | Tags: Case-Based Reasoning, CBR Applications, CBR Framework, CloodCBR, eXiT*CBR, jColibri, myCBR, ProCAKE
@inproceedings{SchultheisZB2023,
title = {An Overview and Comparison of Case-Based Reasoning Frameworks},
author = {Alexander Schultheis and Christian Zeyen and Ralph Bergmann},
url = {https://www.wi2.uni-trier.de/shared/publications/2023_ICCBR_SchultheisZB.pdf},
doi = {10.1007/978-3-031-40177-0_21},
year = {2023},
date = {2023-01-01},
booktitle = {Case-Based Reasoning Research and Development - 31st International Conference, ICCBR 2023, Aberdeen, Scotland, July 17-20, 2023, Proceedings},
volume = {14141},
pages = {327–343},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
abstract = {Case-Based Reasoning (CBR) is a methodology with many applications in industrial and scientific domains. Over the past decades, various frameworks have been developed to facilitate the development of CBR applications. For practitioners and researchers, it is challenging to overview the landscape of existing frameworks with their specific scope and features. This makes it difficult to choose the most suitable framework for specific requirements. To address this issue, this work provides an overview and comparison of CBR frameworks, focusing on five recent, open-source CBR frameworks: CloodCBR, eXiT*CBR, jColibri, myCBR, and ProCAKE. They are compared by supported CBR types, knowledge containers, CBR phases, interfaces, and special features.},
keywords = {Case-Based Reasoning, CBR Applications, CBR Framework, CloodCBR, eXiT*CBR, jColibri, myCBR, ProCAKE},
pubstate = {published},
tppubtype = {inproceedings}
}
Case-Based Reasoning (CBR) is a methodology with many applications in industrial and scientific domains. Over the past decades, various frameworks have been developed to facilitate the development of CBR applications. For practitioners and researchers, it is challenging to overview the landscape of existing frameworks with their specific scope and features. This makes it difficult to choose the most suitable framework for specific requirements. To address this issue, this work provides an overview and comparison of CBR frameworks, focusing on five recent, open-source CBR frameworks: CloodCBR, eXiT*CBR, jColibri, myCBR, and ProCAKE. They are compared by supported CBR types, knowledge containers, CBR phases, interfaces, and special features.