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Relevant bibliographies by topics / Case Base Reasoning (CBR)

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Academic literature on the topic 'Case Base Reasoning (CBR)'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "Case Base Reasoning (CBR)"

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El-Sappagh, Shaker, and Mohammed Mahfouz Elmogy. "Medical Case Based Reasoning Frameworks." International Journal of Decision Support System Technology 8, no. 3 (2016): 31–62. http://dx.doi.org/10.4018/ijdsst.2016070103.

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Case-Based Reasoning (CBR) is one of the most suitable AI techniques for building clinical decision support systems. Medical domain complexity introduces many challenges for building these systems. Building the systems' knowledge base from the Electronic Health Record (EHR), the encoding of case-base knowledge with standard medical ontology, and the handling of vague data are examples of these challenges. Although several advantages of using CBR in medicine have been identified, there are no real systems acceptable to physicians. This systematic review examines the current state of CBR and its

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CHEETHAM, WILLIAM, SIMON SHIU, and ROSINA O. WEBER. "Soft case-based reasoning." Knowledge Engineering Review 20, no. 3 (2005): 267–69. http://dx.doi.org/10.1017/s0269888906000579.

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The aim of this commentary is to discuss the contribution of soft computing—a consortium of fuzzy logic, neural network theory, evolutionary computing, and probabilistic reasoning—to the development of case-based reasoning (CBR) systems. We will describe how soft computing has been used in case representation, retrieval, adaptation, reuse, and case-base maintenance, and then present a brief summary of six CBR applications that use soft computing techniques.

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Mansoul, Abdelhak, and Baghdad Atmani. "Representative Case-Based Retrieval to Support Case-Based Reasoning for Prediction." International Journal of Strategic Decision Sciences 12, no. 3 (2021): 14–35. http://dx.doi.org/10.4018/ijsds.2021070102.

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Case-based reasoning (CBR) is used to resolve a new problem by searching in past similar situations. It is widely used for prediction. However, CBR induces many shortcomings, particularly in its retrieval phase. Many methods and techniques were provided, but have influenced differently the effectiveness of the deduced results. Also, hybridizing different methods emerged to get a better information retrieval and this reasoning manner becomes a ubiquitous issue. The present study has as an objective lending support to CBR to enable enhanced retrieving valid prediction. For this purpose, the stud

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Leake, David B. "Case-based reasoning." Knowledge Engineering Review 9, no. 1 (1994): 61–64. http://dx.doi.org/10.1017/s0269888900006585.

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Case-based reasoning (CBR) systems reason from experience: they solve new problems by retrieving relevant prior cases and adapting them to fit new situations. In 1988 the first case-based reasoning workshop, sponsored by DARPA, identified theoretical foundations and fundamental issues for case-based reasoning research. Since then, much investigation has examined the CBR process itself, the validity of CBR as a cognitive model, and the application of CBR technology. The results of that work include refinements in theories of the case-based reasoning process, psychological evidence for human cas

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Watson, Ian, and Farhi Marir. "Case-based reasoning: A review." Knowledge Engineering Review 9, no. 4 (1994): 327–54. http://dx.doi.org/10.1017/s0269888900007098.

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AbstractCase-Based Reasoning (CBR) is a relatively recent problem solving technique that is attracting increasing attention. However, the number of people with first-hand theoretical or practical experience of CBR is still small. The main objective of this review is to provide a comprehensive overview of the subject to people new to CBR. The paper outlines the development of CBR in the US in the 1980s. It describes the fundamental techniques of CBR and contrasts its approach to that of model-based reasoning systems.1A critical review of currently available CBR software tools is followed by des

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Hunt, John, and Roger Miles. "Hybrid case-based reasoning." Knowledge Engineering Review 9, no. 4 (1994): 383–97. http://dx.doi.org/10.1017/s0269888900007116.

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AbstractThis paper reviews a number of hybrid Case-Based Reasoning (CBR) systems. These systems are hybrid because the CBR components cooperate with one or more “co-reasoners” which employ a different type of reasoning strategy (e.g. qualitative simulation, constraint satisfaction, etc.). In this paper, we propose that CBR is in fact an inherently hybrid process. We review a number of systems and identify three classes of architecture which have been used for hybrid systems. We believe that to successfully exploit a co-reasoner within a CBR system it is necessary to analyse where, when, why an

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Jian, Yu Mei, and Ming Chen. "An Intelligent Aerobic Expert System Combining CBR and RBR." Applied Mechanics and Materials 321-324 (June 2013): 1977–81. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.1977.

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According to the highly dependent on breeding characteristics of the aquatic products, this paper builds an intelligent aerobic expert system which combines two kinds of artificial intelligence technique, case based reasoning (CBR) and rule based reasoning (RBR). After retrocede the collection data, firstly, the case base is retrieved to find the similar solutions. Only when the solution cases can not be obtained from the case base or the case solutions are not satisfactory, is the RBR system used to solve problem and then the reasoning result is stored in the case base for future use. The int

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PLAZA, ENRIC, and LORRAINE MCGINTY. "Distributed case-based reasoning." Knowledge Engineering Review 20, no. 3 (2005): 261–65. http://dx.doi.org/10.1017/s0269888906000683.

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Distribution of resources within case-based reasoning (CBR) architectures is beneficial in a variety of application contexts. This article briefly discusses some of the approaches that fall under the heading of distributed CBR, and their general impact.

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MARLING, CINDY, EDWINA RISSLAND, and AGNAR AAMODT. "Integrations with case-based reasoning." Knowledge Engineering Review 20, no. 3 (2005): 241–45. http://dx.doi.org/10.1017/s026988890600066x.

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This commentary succinctly summarizes work in integrating case-based reasoning (CBR) with other reasoning modalities. Including CBR in mixed mode approaches promotes synergies and benefits beyond those achievable using CBR or other individual reasoning approaches alone. Numerous examples of hybrid systems, with pointers to significant references, are provided.

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Rumui, Nelson, Agus Harjoko, and Aina Musdholifah. "Case-Based Reasoning for Stroke Disease Diagnosis." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 12, no. 1 (2018): 33. http://dx.doi.org/10.22146/ijccs.26331.

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Stroke is a type of cerebrovascular disease that occurs because blood flow to the brain is disrupted. Examination of stroke accurately using CT scan, but the tool is not always available, so it can be done by the Siriraj Score. Each type of stroke has similar symptoms so doctors should re-examine similar cases prior to diagnosis. The hypothesis of the Case-based reasoning (CBR) method is a similar problems having similar solution.This research implements CBR concept using Siriraj score, dense index and Jaccard Coeficient method to perform similarity calculation between cases.The test is using

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Dissertations / Theses on the topic "Case Base Reasoning (CBR)"

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Wong, Fai. "Case-based reasoning (CBR) supporting P.O. Box Automation System." Thesis, University of Macau, 1999. http://umaclib3.umac.mo/record=b1636998.

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Zhang, Zhong. "Static and dynamic feature weighting in case-based reasoning, CBR." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/mq24280.pdf.

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Kianifar, Arash. "Case-based reasoning in postoperative pain treatment." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-12169.

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Even today, with modern medicine and technology, post-operative pain still exists as anmajor issue in modern treatment. A lot of research efforts have been made, in order toimprove pain outcome for patients that has undergone surgery[18][15].Even though physician's and doctors are well educated, the success rate is aboutapproximately 70 %, still there are patients that experience severe pain, after they haveundergone surgery. There could be several reasons to this, for example, lack of methods orsupport should be amongst other things, factors to consider[18].The problem has been to initiate a

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Larsson, Carl. "Case Representation Methodology for a Scalable Case-Based Reasoning." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-41116.

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Case-Based Reasoning (CBR) is an Artificial Intelligence (AI) methodology and a growing field of research. CBR uses past experiences to help solve new problems the system faces. To do so CBR is comprised of a few core parts, such as case representation, case library, case retrieval, and case adaptation. This thesis will focus on the case representation aspect of CBR systems and presents a scalable case representation for big data environments. One aspect of focus on big data environments is also the focus of a MapReduce environment. MapReduce is a software framework enabling the use of a Map a

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Bjurén, Johan. "USING CASE-BASED REASONING FOR PREDICTING ENERGY USAGE." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-9436.

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In this study, the inability to in a future meet the electricity demand and the urge to change the consumption behavior considered. In a smart grid context there are several possible ways to do this. Means include ways to increase the consumer’s awareness, add energy storages or build smarter homes which can control the appliances. To be able to implement these, indications on how the future consumption will be could be useful. Therefore we look further into how a framework for short-term consumption predictions can be created using electricity consumption data in relation to external factors.

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Nordström, Philip, and Mario Mamic. "Automatiserade kostnadsberäkningar för plattformningsverktyg." Thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH, Maskinteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-21832.

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I dagsläget saknar Thor Ahlgren AB underlag för att på ett enkelt sätt kunna kalkylera och uppskatta priset för ett pressverktyg. När företaget får en förfrågan från kund angående huruvida de kan producera en detalj måste de återkomma med en offert till kunden där ett pris för verktygskostnaden är inkluderad. Innan ett pris kan offereras till kund måste Thor Ahlgren AB kontakta en verktygsmakare för prisförslag på verktyget och denna process kan variera i tid. Syftet med arbetet är att förkorta eller eliminera denna process och på så vis kunna offerera pris för konstr

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Khajotia, Burzin K. "CASE BASED REASONING – TAYLOR SERIES MODEL TO PREDICT CORROSION RATE IN OIL AND GAS WELLS AND PIPELINES." Ohio University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1173828758.

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Richmond, Doug. "Lessons Learned from Designing a Comprehensive Case-Based Reasoning (CBR) Tool for Support of Complex Thinking." Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/27693.

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This research study focused on learning lessons from the experience of designing a comprehensive case-based reasoning (CBR) tool for support of complex thinking skills. Theorists have historically identified, analyzed, and classified different thinking processes and skills. Thinking skills have been increasingly emphasized in national standards, state testing, curricula, teaching and learning resources, and research agendas. Complex thinking is the core of higher-order thinking. Complex thinking is engaged when different types of thinking and action converge to resolve a real-world, ill-struct

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Kronberg, F., A. Weiner, T. Morgan, et al. "Document Retrieval Triggered by Spacecraft Anomaly: Using the Kolodner Case-Based Reasoning (CBR) Paradigm to Design a Fault-Induced Response System." International Foundation for Telemetering, 1996. http://hdl.handle.net/10150/611459.

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International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California<br>We report on the initial design and development of a prototype computer-mediated response system, the Fault Induced Document Officer (FIDO), at the UC Berkeley Center for EUV Astrophysics (CEA) Extreme Ultraviolet Explorer project (EUVE). Typical 24x7 staffed spacecraft operations use highly skilled expert teams to monitor current ground systems and spacecraft state for responding to anomalous ground system and spacecraft conditions. Response to groun

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Ruiz, Ordóñez Magda Liliana. "Multivariate Statistical Process Control and Case-Based Reasoning for situation assessment of Sequencing Batch Reactors." Doctoral thesis, Universitat de Girona, 2008. http://hdl.handle.net/10803/7746.

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ABSRACT<br/><br/>This thesis focuses on the monitoring, fault detection and diagnosis of Wastewater Treatment Plants (WWTP), which are important fields of research for a wide range of engineering disciplines. <br/><br/>The main objective is to evaluate and apply a novel artificial intelligent methodology based on situation assessment for monitoring and diagnosis of Sequencing Batch Reactor (SBR) operation. To this end, Multivariate Statistical Process Control (MSPC) in combination with Case-Based Reasoning (CBR) methodology was developed, which was evaluated on three different SBR (pilot and l

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Books on the topic "Case Base Reasoning (CBR)"

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Patterson, William Robert David. Introspective techniques for maintaining retrieval knowledge in case-base reasoning. The Author], 2001.

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Book chapters on the topic "Case Base Reasoning (CBR)"

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Richter, Michael M., and Rosina O. Weber. "Textual CBR." In Case-Based Reasoning. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40167-1_17.

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Richter, Michael M., and Rosina O. Weber. "Conversational CBR." In Case-Based Reasoning. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40167-1_20.

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Richter, Michael M., and Rosina O. Weber. "Advanced CBR Elements." In Case-Based Reasoning. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40167-1_12.

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Richter, Michael M., and Rosina O. Weber. "Basic CBR Elements." In Case-Based Reasoning. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40167-1_2.

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Lenz, Mario, André Hübner, and Mirjam Kunze. "Textual CBR." In Case-Based Reasoning Technology. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-69351-3_5.

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Gierl, Lothar, Mathias Bull, and Rainer Schmidt. "CBR in Medicine." In Case-Based Reasoning Technology. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-69351-3_11.

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Börner, Katy. "CBR for Design." In Case-Based Reasoning Technology. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-69351-3_8.

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Abdel-Aziz, Amira, and Eyke Hüllermeier. "Case Base Maintenance in Preference-Based CBR." In Case-Based Reasoning Research and Development. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24586-7_1.

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Bergmann, Ralph, Héctor Muñoz-Avila, Manuela Veloso, and Erica Melis. "CBR Applied to Planning." In Case-Based Reasoning Technology. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-69351-3_7.

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Bergmann, Ralph, and Klaus-Dieter Althoff. "Methodology for Building CBR Applications." In Case-Based Reasoning Technology. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-69351-3_12.

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Conference papers on the topic "Case Base Reasoning (CBR)"

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Khajotia, Burzin, Dusan Sormaz, and Srdjan Nesic. "Case-based Reasoning Model of CO2 Corrosion Based on Field Data." In CORROSION 2007. NACE International, 2007. https://doi.org/10.5006/c2007-07553.

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Abstract An important aspect in corrosion prediction for oil and gas wells and pipelines is to obtain a realistic estimate of the corrosion rate. Corrosion rate prediction involves developing a predictive model that utilizes commonly available operational parameters, existing lab/field data and theoretical models to obtain realistic assessments of corrosion rates. The Case-based Reasoning (CBR) model for CO2 corrosion prediction is designed to mimic the approach of experienced field corrosion personnel. The model takes knowledge of corrosion rates for existing cases and uses CBR techniques and

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Gould, Adam, Guilherme Paulino-Passos, Seema Dadhania, Matthew Williams, and Francesca Toni. "Preference-Based Abstract Argumentation for Case-Based Reasoning." In 21st International Conference on Principles of Knowledge Representation and Reasoning {KR-2023}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/kr.2024/37.

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In the pursuit of enhancing the efficacy and flexibility of interpretable, data-driven classification models, this work introduces a novel incorporation of user-defined preferences with Abstract Argumentation and Case-Based Reasoning (CBR). Specifically, we introduce Preference-Based Abstract Argumentation for Case-Based Reasoning (which we call AA-CBR-P), allowing users to define multiple approaches to compare cases with an ordering that specifies their preference over these comparison approaches. We prove that the model inherently follows these preferences when making predictions and show th

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Roberge, P. R., and K. R. Trethewey. "An Indexing System of Corrosion Failures for Case-Based Reasoning." In CORROSION 1996. NACE International, 1996. https://doi.org/10.5006/c1996-96359.

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Abstract The difficulties associated with the committal of human expert knowledge to computers for the development of more effective knowledge-based systems have raised the possibility of mimicking the process of reasoning from previous experiences. Experts are known to make proficient decisions based more upon analogy with similar events and situations than the kind of sequential mechanisms used in many algorithmic approaches. For many years, both law and business schools have used cases as the foundation for knowledge in their respective disciplines. Computer reasoning by analogy, a techniqu

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VuThi, Thuy, and Waiter F. Bogaerts. "Case-Based Reasoning in Corrosion Engineering." In CORROSION 1998. NACE International, 1998. https://doi.org/10.5006/c1998-98403.

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Abstract In this paper, the background and principles of case-based reasoning are described, and we discuss how the use of a CBR1(1) approach to data retrieval allows us to provide mors intelligent support during the materials selection process as compared to the support offered by more traditional databases or conventional expert systems. This will be illustrated in particular for two case-based reasoning applications we recently developed: (a) for selecting materials corresponding to a given set of required (physical) properties and specifications, and (b) for the more challenging task of se

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Arieli, Ofer, Kees van Berkel, Badran Raddaoui, and Christian Strasser. "Deontic Reasoning Based on Inconsistency Measures." In 21st International Conference on Principles of Knowledge Representation and Reasoning {KR-2023}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/kr.2024/7.

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Conflicts are inherent to normative systems. In this paper, we explore a novel approach to normative reasoning by quantifying the amount of conflicts within normative systems. We refine the idea from classical logic, according to which a formula is a consequence of a knowledge base in case its negation renders the knowledge base inconsistent. In our approach, whether a formula is a logical consequence depends, for instance, on its negation's marginal contribution to the inconsistency of the given knowledge base. Accordingly, various inconsistency measures and corresponding (nonmonotonic and pa

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Juarez, Jose M., Susan Craw, J. Ricardo Lopez-Delgado, and Manuel Campos. "Maintenance of Case Bases: Current Algorithms after Fifty Years." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/770.

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Case-Based Reasoning (CBR) learns new knowledge from data and so can cope with changing environments. CBR is very different from model-based systems since it can learn incrementally as new data is available, storing new cases in its case-base. This means that it can benefit from readily available new data, but also case-base maintenance (CBM) is essential to manage the cases, deleting and compacting the case-base. In the 50th anniversary of CNN (considered the first CBM algorithm), new CBM methods are proposed to deal with the new requirements of Big Data scenarios. In this paper, we present a

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Qin, Xiaoli, and William C. Regli. "Applying Case-Based Reasoning to Mechanical Bearing Design." In ASME 2000 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/detc2000/dfm-14011.

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Abstract Case-Based Reasoning (CBR) provides a promising methodology for solving many complex engineering design problems. CBR is based on the idea that past problem-solving experiences can be reused and learned from in solving new problems. This paper presents an overview of a CBR design system to assist human engineers in performing mechanical bearing design. It retrieves previously designed cases from a case-base and uses adaptation techniques to adapt them to satisfy the current problem requirements. Our approach combines parametric adaptations and constraint satisfaction adaptations. The

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Paulino-Passos, Guilherme, and Francesca Toni. "Monotonicity and Noise-Tolerance in Case-Based Reasoning with Abstract Argumentation." In 18th International Conference on Principles of Knowledge Representation and Reasoning {KR-2021}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/kr.2021/48.

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Recently, abstract argumentation-based models of case-based reasoning (AA-CBR in short) have been proposed, originally inspired by the legal domain, but also applicable as classifiers in different scenarios. However, the formal properties of AA-CBR as a reasoning system remain largely unexplored. In this paper, we focus on analysing the non-monotonicity properties of a regular version of AA-CBR (that we call AA-CBR_>). Specifically, we prove that AA-CBR_> is not cautiously monotonic, a property frequently considered desirable in the literature. We then define a variation of AA-CBR_> w

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Banga, Karan, and Shun Takai. "A Comparison of Case-Based Reasoning and Regression Analysis Approaches for Cost Uncertainty Modeling." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28232.

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This paper presents cost uncertainty modeling for a concept selection using case-based reasoning (CBR) and compares this method with the regression analysis approach. During the product development stage, a number of decisions must be made under uncertainty, including selection of an ideal product concept. The cost of a concept, i.e., the cost of the final product developed from a concept, is a key factor influencing the choice of an ideal concept. The CBR approach creates a knowledge base (or database) containing past cases, defines a new case, retrieves cases similar to the new case, and ada

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Chang, Guanghsu A., Cheng-Chung Su, and John W. Priest. "Retrieving Assembly Part Design Using Case-Based Reasoning and Genetic Algorithms." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-80334.

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Artificial intelligence (AI) approaches have been successfully applied to many fields. Among the numerous AI approaches, Case-Based Reasoning (CBR) is an approach that mainly focuses on the reuse of knowledge and experience. However, little work is done on applications of CBR to improve assembly part design. Similarity measures and the weight of different features are crucial in determining the accuracy of retrieving cases from the case base. To develop the weight of part features and retrieve a similar part design, the research proposes using Genetic Algorithms (GAs) to learn the optimum feat

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Reports on the topic "Case Base Reasoning (CBR)"

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Erbacher, Robert F., and Steve E. Hutchinson. Extending Case-Based Reasoning (CBR) Approaches to Semi-automated Network Alert Reporting. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada584553.

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Pasupuleti, Murali Krishna. Stochastic Computation for AI: Bayesian Inference, Uncertainty, and Optimization. National Education Services, 2025. https://doi.org/10.62311/nesx/rriv325.

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Abstract: Stochastic computation is a fundamental approach in artificial intelligence (AI) that enables probabilistic reasoning, uncertainty quantification, and robust decision-making in complex environments. This research explores the theoretical foundations, computational techniques, and real-world applications of stochastic methods, focusing on Bayesian inference, Monte Carlo methods, stochastic optimization, and uncertainty-aware AI models. Key topics include probabilistic graphical models, Markov Chain Monte Carlo (MCMC), variational inference, stochastic gradient descent (SGD), and Bayes

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