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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
- 2.
- 3.
- 4.
- 5.
- 6.
A complete overview table is available at: https://git.opendfki.de/easy/overview-and-comparison-of-cbr-frameworks/-/blob/main/Overview-Table.pdf.
References
Aamodt, A., Plaza, E.: Case-based reasoning: foundational issues, methodological variations, and system approaches. AI Commun. 7(1), 39–59 (1994)
Abásolo, C., Plaza, E., Arcos, J.-L.: Components for case-based reasoning systems. In: Escrig, M.T., Toledo, F., Golobardes, E. (eds.) CCIA 2002. LNCS (LNAI), vol. 2504, pp. 1–16. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-36079-4_1
Atanassov, A., Antonov, L.: Comparative analysis of case based reasoning software frameworks jColibri and myCBR. J. Chem. Technol. Metall. 47(1), 83–90 (2012)
Bach, K., Althoff, K.-D.: Developing case-based reasoning applications using myCBR 3. In: Agudo, B.D., Watson, I. (eds.) ICCBR 2012. LNCS (LNAI), vol. 7466, pp. 17–31. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-32986-9_4
Bach, K., Mathisen, B.M., Jaiswal, A.: Demonstrating the myCBR rest API. In: 27th ICCBR Workshop Proceedings. CEUR Workshop Proceedings, vol. 2567, pp. 144–155. CEUR-WS.org (2019)
Bach, K., Sauer, C.S., Althoff, K., Roth-Berghofer, T.: Knowledge modeling with the open source tool myCBR. In: 21st ECAI Workshop Proceedings. CEUR Workshop Proceedings, vol. 1289. CEUR-WS.org (2014)
Begum, S., Ahmed, M.U., Funk, P., Xiong, N., Folke, M.: Case-based reasoning systems in the health sciences: a survey of recent trends and developments. IEEE Trans. Syst. Man Cybern. Part C 41(4), 421–434 (2011)
Bello-Tomás, J.J., González-Calero, P.A., Díaz-Agudo, B.: JColibri: an object-oriented framework for building CBR systems. In: Funk, P., González Calero, P.A. (eds.) ECCBR 2004. LNCS (LNAI), vol. 3155, pp. 32–46. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-28631-8_4
Bergmann, R., Gil, Y.: Similarity assessment and efficient retrieval of semantic workflows. Inf. Syst. 40, 115–127 (2014)
Bergmann, R., Grumbach, L., Malburg, L., Zeyen, C.: ProCAKE: a process-oriented case-based reasoning framework. In: 27th ICCBR Workshop Proceedings (2019)
Bogaerts, S., Leake, D.: Technical report 617 IUCBRF: a framework for rapid and modular case-based reasoning system development report version 1.0. IU Bloomington (2005)
Bogaerts, S., Leake, D.B.: Increasing AI project effectiveness with reusable code frameworks: a case study using IUCBRF. In: 18th FLAIRS. FloridaOJ, pp. 2–7. AAAI Press (2005)
Bruland, T., Aamodt, A., Langseth, H.: Architectures integrating case-based reasoning and Bayesian networks for clinical decision support. In: Shi, Z., Vadera, S., Aamodt, A., Leake, D. (eds.) IIP 2010. IAICT, vol. 340, pp. 82–91. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-16327-2_13
Díaz-Agudo, B., González-Calero, P.A., Recio-García, J.A., Sánchez-Ruiz-Granados, A.A.: Building CBR systems with jColibri. SCP 69(1–3), 68–75 (2007)
Eisenstadt, V., Langenhan, C., Althoff, K.D.: Generation of floor plan variations with convolutional neural networks and case-based reasoning - an approach for unsupervised adaptation of room configurations within a framework for support of early conceptual design. In: eCAADe SIGraDi Conference, Porto (2019)
ElKafrawy, P., Mohamed, R.A.: Comparative study of case-based reasoning software. IJSRM 1(6), 224–233 (2015)
Grumbach, L., Bergmann, R.: Towards case-based deviation management for flexible workflows. In: Jäschke, R., Weidlich, M. (eds.) LWDA 2019. CEUR Workshop Proceedings, vol. 2454, pp. 241–252. CEUR-WS.org (2019)
He, W., Wang, F.: Integrating a case-based reasoning shell and web 2.0: design recommendations and insights. World Wide Web 19(6), 1231–1249 (2016). https://doi.org/10.1007/s11280-015-0380-y
Heilala, J., et al.: Ambient intelligence based monitoring and energy efficiency optimization system. In: ISAM 2011, pp. 1–6. IEEE (2011)
Hinkle, D., Toomey, C.: Applying case-based reasoning to manufacturing. AI Mag. 16(1), 65–65 (1995)
Hoffmann, M., Bergmann, R.: Using graph embedding techniques in process-oriented case-based reasoning. Algorithms 15(2), 27 (2022)
Hundt, A., Reuss, P., Sauer, C.S., Roth-Berghofer, T.: Knowledge modelling and maintenance in myCBR3. In: 16th LWA Workshop Proceedings. CEUR Workshop Proceedings, vol. 1226, pp. 264–275. CEUR-WS.org (2014)
Husni, H.S., Ramadhan, A., Abdurachman, E., Trisetyarso, A.: Indonesia digital government auditing model using rule based and cloud case-based reasoning. Int. J. Sci. Technol. Res. 1(2), 60–63 (2022)
Jaczynski, M.: A framework for the management of past experiences with time-extended situations. In: 6th CIKM Proceedings, pp. 32–39. ACM (1997)
Jaczynski, M., Trousse, B.: An object-oriented framework for the design and the implementation of case-based reasoners. In: CBR Workshop Proceedings (1998)
Kolodner, J.L.: Reconstructive memory: a computer model. Cogn. Sci. 7(4), 281–328 (1983)
Kumar, R., Schultheis, A., Malburg, L., Hoffmann, M., Bergmann, R.: Considering inter-case dependencies during similarity-based retrieval in process-oriented case-based reasoning. In: 35th FLAIRS. FloridaOJ (2022)
Lebowitz, M.: Memory-based parsing. AI 21(4), 363–404 (1983)
López, B., et al.: Intelligent system for premature babies healthcare at home based on case-based reasoning. In: 2nd IWBBIO, pp. 1278–1289. Copicentro Editorial (2014)
López, B., Pous, C.: eXiT*CBR: a tool supporting RRI. In: 21st CCIA. Frontiers in Artificial Intelligence and Applications, vol. 308, pp. 176–179. IOS Press (2018)
López, B., Pous, C., Gay, P., Pla, A., Sanz, J., Brunet, J.: eXiT*CBR: a framework for case-based medical diagnosis development and experimentation. Artif. Intell. Med. 51(2), 81–91 (2011)
López, B., et al.: APPRAISE-RS: automated, updated, participatory, and personalized treatment recommender systems based on grade methodology. Heliyon 9(2), e13074 (2023)
López, B., Pous, C., Plá, A., Gay, P., Brunet, J.: Breast cancer prognosis through CBR. In: 27th ICCBR Workshop Proceedings, pp. 105–110 (2012)
Malburg, L., Brand, F., Bergmann, R.: Adaptive management of cyber-physical workflows by means of case-based reasoning and automated planning. In: Sales, T.P., Proper, H.A., Guizzardi, G., Montali, M., Maggi, F.M., Fonseca, C.M. (eds.) EDOC 2022. LNBIP, vol. 466, pp. 79–95. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-26886-1_5
Mark, W.S.: Case-based reasoning for autoclave management. In: CBR Workshop Proceedings, pp. 176–180. DARPA - Information Science (1989)
Martín, A., León, C.: Expert knowledge management based on ontology in a digital library. In: 12th ICEIS Proceedings, pp. 291–298. SciTePress (2010)
Müller, G., Bergmann, R.: A cluster-based approach to improve similarity-based retrieval for process-oriented case-based reasoning. In: 21st ECAI, vol. 263, pp. 639–644. IOS Press (2014)
Nguyen, T., Czerwinski, M., Lee, D.: Compaq QuickSource: providing the consumer with the power of artificial intelligence. In: IAAIC Proceedings, pp. 142–151 (1993)
Nkisi-Orji, I., Palihawadana, C., Wiratunga, N., Corsar, D., Wijekoon, A.: Adapting semantic similarity methods for case-based reasoning in the cloud. In: Keane, M.T., Wiratunga, N. (eds.) ICCBR 2022. LNAI, vol. 13405, pp. 125–139. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-14923-8_9
Nkisi-Orji, I., Wiratunga, N., Palihawadana, C., Recio-García, J.A., Corsar, D.: Clood CBR: towards microservices oriented case-based reasoning. In: Watson, I., Weber, R. (eds.) ICCBR 2020. LNCS (LNAI), vol. 12311, pp. 129–143. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-58342-2_9
Palihawadana, C., Nkisi-Orji, I., Wiratunga, N., Corsar, D., Wijekoon, A.: Introducing Clood CBR: a cloud based CBR framework. In: 30th ICCBR Workshop Proceedings. CEUR Workshop Proceedings, vol. 3389, pp. 233–234. CEUR-WS.org (2022)
Peixoto, T.F., Martinazzo, L.A., Weber, R.O.: Cyberinfrastructure requirements for research communities. In: 7th CIKI, vol. 1 (2017)
Pla, A., López, B., Gay, P., Pous, C.: eXiT*CBRv.2: distributed case-based reasoning tool for medical prognosis. Decis. Support Syst. 54(3), 1499–1510 (2013)
Recio, J.A., Sánchez, A., Díaz-Agudo, B., González-Calero, P.: jColibri 1.0 in a nutshell. A software tool for designing CBR systems. In: 10th UKCBR Workshop Proceedings, pp. 1–11 (2005)
Recio-Garcia, J.A., Díaz-Agudo, B., Jorro-Aragoneses, J.L., Kazemi, A.: Intelligent control system for back pain therapy. In: Aha, D.W., Lieber, J. (eds.) ICCBR 2017. LNCS (LNAI), vol. 10339, pp. 287–301. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61030-6_20
Recio-García, J.A., González-Calero, P.A., Díaz-Agudo, B.: jColibri2: a framework for building case-based reasoning systems. SCP 79, 126–145 (2014)
Reuss, P., Stram, R., Althoff, K.-D., Henkel, W., Henning, F.: Knowledge engineering for decision support on diagnosis and maintenance in the aircraft domain. In: Nalepa, G.J., Baumeister, J. (eds.) Synergies Between Knowledge Engineering and Software Engineering. AISC, vol. 626, pp. 173–196. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-64161-4_9
Richter, M.M.: Knowledge containers. In: Readings in CBR. MKP (2003)
Sabri, Q.U., Bayer, J., Ayzenshtadt, V., Bukhari, S.S., Althoff, K.D., Dengel, A.: Semantic pattern-based retrieval of architectural floor plans with case-based and graph-based searching techniques and their evaluation and visualization. In: ICPRAM, pp. 50–60 (2017)
Schoenborn, J.M., Weber, R.O., Aha, D.W., Cassens, J., Althoff, K.D.: Explainable case-based reasoning: a survey. In: AAAI-2021 Workshop Proceedings (2021)
Schoenborn, J.M., Reuss, P., Wenzel, C., Althoff, K.: Towards a case-based decision support system for recruiting processes using T-shapes. In: Modellierung-C 2020. CEUR Workshop Proceedings, vol. 2542, pp. 165–171. CEUR-WS.org (2020)
Schultheis, A., Hoffmann, M., Malburg, L., Bergmann, R.: Explanation of similarities in process-oriented case-based reasoning by visualization. In: Massie, S., Chakraborti, S. (eds.) ICCBR 2023. LNAI, vol. 14141, pp. 53–68. Springer, Cham (2023)
Schulz, S.: CBR-works - a state-of-the-art shell for case-based application building. In: 7th GWCBR Proceedings, vol. 99, pp. 3–12. Citeseer (1999)
Schumacher, J.: Empolis Orenge - an open platform for knowledge management applications. In: 1st German Workshop on Experience Mgmt, pp. 61–62. GI (2002)
Stahl, A., Roth-Berghofer, T.R.: Rapid prototyping of CBR applications with the open source tool myCBR. In: Althoff, K.-D., Bergmann, R., Minor, M., Hanft, A. (eds.) ECCBR 2008. LNCS (LNAI), vol. 5239, pp. 615–629. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-85502-6_42
Stram, R., Reuss, P., Althoff, K.-D.: Dynamic case bases and the asymmetrical weighted one-mode projection. In: Cox, M.T., Funk, P., Begum, S. (eds.) ICCBR 2018. LNCS (LNAI), vol. 11156, pp. 385–398. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-01081-2_26
Thakur, N., Chhabra, T., Verma, D., Kumar, D., Dayal, M.: Case based reasoning: a comparative analysis of CBR tools. IJIRCST 4, 11190–11196 (2016)
Unsworth, R., et al.: Safety and efficacy of an adaptive bolus calculator for type 1 diabetes: a randomized controlled crossover study. Dia. Technol. Ther 25(6), 414–425 (2023)
Watson, I.D.: Applying Case-Based Reasoning - Techniques for the Enterprise Systems. MKP (1997)
Watson, I.D., Marir, F.: Case-based reasoning: a review. Knowl. Eng. Rev. 9(4), 327–354 (1994)
Wenzel, C., Reuss, P., Rose, K., Althoff, K.D.: Multi-agent, case-based configuration of custom-built racing cars. In: 19th UKCBR Workshop Proceedings (2014)
Wijekoon, A., Wiratunga, N., Palihawadana, C., Nkisi-Orji, I., Corsar, D., Martin, K.: iSee: intelligent sharing of explanation experience by users for users. In: 28th IUI Companion Proceedings, pp. 79–82 (2023)
Zeyen, C., Malburg, L., Bergmann, R.: Adaptation of scientific workflows by means of process-oriented case-based reasoning. In: Bach, K., Marling, C. (eds.) ICCBR 2019. LNCS (LNAI), vol. 11680, pp. 388–403. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-29249-2_26
Zeyen, C., Müller, G., Bergmann, R.: Conversational process-oriented case-based reasoning. In: Aha, D.W., Lieber, J. (eds.) ICCBR 2017. LNCS (LNAI), vol. 10339, pp. 403–419. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61030-6_28
Acknowledgments
We would like to thank the following people for contributing to the compilation of the CBR framework fact sheets: Ikechukwu Nkisi-Orji and Chamath Palihawadana (CloodCBR), Beatriz López, Oscar Raya, and Jonah Fernández (eXiT*CBR), Juan Antonio Recio García (jColibri), and Pascal Reuss (myCBR). This work is funded by the Federal Ministry for Economic Affairs and Climate Action under grant No. 01MD22002C EASY.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Schultheis, A., Zeyen, C., Bergmann, R. (2023). An Overview and Comparison of Case-Based Reasoning Frameworks. In: Massie, S., Chakraborti, S. (eds) Case-Based Reasoning Research and Development. ICCBR 2023. Lecture Notes in Computer Science(), vol 14141. Springer, Cham. https://doi.org/10.1007/978-3-031-40177-0_21
Download citation
DOI: https://doi.org/10.1007/978-3-031-40177-0_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-40176-3
Online ISBN: 978-3-031-40177-0
eBook Packages: Computer ScienceComputer Science (R0)