Search the World's Largest Database of Information Science & Technology Terms & Definitions
InfInfoScipedia LogoScipedia
A Free Service of IGI Global Publishing House
Below please find a list of definitions for the term that
you selected from multiple scholarly research resources.

What is Case-Based Reasoning

Handbook of Research on E-Business Standards and Protocols: Documents, Data and Advanced Web Technologies
Case-based reasoning is dealing with the “intelligent” reuse of knowledge from already solved old problems (“cases”) and its adaptation to similar, but new und yet unsolved problems.
Published in Chapter:
Ontologies for Guaranteeing the Interoperability in e-Business: A Business Economics Point of View
Stephan Zelewski (University of Duisburg-Essen, Institute for Production and Industrial Information Management, Germany), Adina Silvia Bruns (University of Duisburg-Essen, Institute for Production and Industrial Information Management, Germany), and Martin Kowalski (University of Duisburg-Essen, Institute for Production and Industrial Information Management, Germany)
DOI: 10.4018/978-1-4666-0146-8.ch008
Abstract
For e-business, the computer-based processing of value-creation, especially for knowledge-intensive business processes, plays a prominent role with the help of modern information and communication techniques. At least since the further development of the classical Internet for the Semantic Web, the content-based knowledge processing and knowledge transfer have gained more importance. In this chapter it is shown that ontologies represent an auspicious instrument to ensure the interoperability of information and communication systems that have to work together on the work-sharing development of knowledge-intensive business processes. Ontologies become important when agents with heterogeneous knowledge backgrounds co-operate on such business processes. Firstly, the complex and often ill-considered use of the definition of ontology will be discussed critically and its meaning specified. Thereupon it will be shown (with the help of two application areas) how ontologies can be used effectively to support knowledge-intensive business processes in e-business. On the one hand, the chapter is concerned with the management of knowledge of competences, which agents have to have a command of for successful process execution. On the other hand, it is about the management of know-how, which has already been collected from completed projects and should be reused in new projects.
Full Text Chapter Download: US $37.50 Add to Cart
More Results
Handling Bipolar Queries in Fuzzy Information Processing
Inference or problem-solving technique based on the similarity between the current problem and previously solved ones that are stored in a repository. Its principle relies on the idea that the more similar two problems, the more similar their solution.
Full Text Chapter Download: US $37.50 Add to Cart
Pre-Service Computer Teachers as 3D Educational Game Designers
The theory of memory and learning which aims to explain how people remember and use their memories in order to solve new problems (Schank et al., 1999). Solving new problems by using or adapting the solutions of the old problems (Riesbeck & Schank, 1989).
Full Text Chapter Download: US $37.50 Add to Cart
Big Data, Semantics, and Policy-Making: How Can Data Dynamics Lead to Wiser Governance?
Aims to (re)use previous experiences defined as codified rules and strong domain models (cases) to deal with challenged situation using similarity retrieval techniques.
Full Text Chapter Download: US $37.50 Add to Cart
Artificial Intelligence and Investing
The process of solving new problems based on successful past solutions to similar problems.
Full Text Chapter Download: US $37.50 Add to Cart
Ambient-Intelligent Decision Support System (Am-IDSS) for Smart Manufacturing
The process of learning to solve new problems based on the solutions of similar past problems.
Full Text Chapter Download: US $37.50 Add to Cart
Web Development Effort Estimation: An Empirical Analysis
Assumes that similar problems provide similar solutions. It provides estimates by comparing the characteristics of the current project to be estimated against a library of historical information from completed projects with a known effort (case base).
Full Text Chapter Download: US $37.50 Add to Cart
A New Approach to Reducing Social Engineering Impact
A technique that helps solving a specific problem based on past similar ones.
Full Text Chapter Download: US $37.50 Add to Cart
A Fabric Resource Management System (FRMS) for Fashion Product Development
A knowledge-based artificial intelligence technique which solves problems based on knowledge and experience gained from solving similar past problems.
Full Text Chapter Download: US $37.50 Add to Cart
Decision Support for Smart Manufacturing
The process of learning to solve new problems based on the solutions of similar past problems.
Full Text Chapter Download: US $37.50 Add to Cart
Semantic Framework for an Efficient Information Retrieval in the E-Government Repositories
A technique for problem/search solving which looks for previous examples, which are similar to the current problem/search.
Full Text Chapter Download: US $37.50 Add to Cart
Applying Artificial Intelligence to Financial Investing
The process of solving new problems based on successful past solutions to similar problems.
Full Text Chapter Download: US $37.50 Add to Cart
A Case-Based-Reasoning System for Feature Selection and Diagnosing Asthma
Process of arriving at the solution of a new problem on the basis of the solutions of previously-solved similar problems, such as when a doctor, lawyer, or mechanic relies on experience to remedy a current situation. In comparison to rule based systems (see expert system) which are useful where only one or a few solutions to a problem are possible, case based systems are useful in solving complex problems with many alternative solutions.
Full Text Chapter Download: US $37.50 Add to Cart
Applying Artificial Intelligence to Financial Investing
The process of solving new problems based on successful past solutions to similar problems.
Full Text Chapter Download: US $37.50 Add to Cart
Business Processes, Dynamic Contexts, Learning
Technique to store solutions for solving actual and similar problems.
Full Text Chapter Download: US $37.50 Add to Cart
Planning Agent for Geriatric Residences
A type of reasoning based on the use of past experiences. The purpose of CBR systems is to solve new problems by adapting solutions that have been used to solve similar problems in the past. The main concept when working with CBR is the concept of case, which can be defined as a past experience.
Full Text Chapter Download: US $37.50 Add to Cart
Achieving Classroom Excellence in a Virtual Classroom
Case-based reasoning resulting from cases that provide students an opportunity to understand the “why” of real-world situations. Multiple cases promote deep learning because students see how prior solutions can be adapted to new problems or how prior cases are related to new cases.
Full Text Chapter Download: US $37.50 Add to Cart
Framework for Reusable Test Case Generation in Software Systems Testing
The main idea of case-based reasoning (CBR) is to adapt solutions that were used to solve previous problems and use them for solving latest problems (cases). A CBR system consists of a case base (which is the set of all cases that are known to the system) and an inferencing mechanism to drive a solution from the stored cases.
Full Text Chapter Download: US $37.50 Add to Cart
A Trust Case-Based Model Applied to Agents Collaboration
An approach that solves new problems using solutions applied in previous cases.
Full Text Chapter Download: US $37.50 Add to Cart
Web Service in Knowledge Management for Global Software Development
Case-based reasoning (CBR) is one of the useful mechanisms for both modeling human reasoning and building intelligent software application systems. The basic principle of case-based reasoning systems is that of solving problems by adapting the solution of similar problems solved in the past. A CBR system consists of a case base , which is the set of all cases that are known to the system. The case base can be thought of as a specific kind of knowledge base that contains only cases. When a new case is presented to the system, it checks the case base for similar cases that are most relevant to the case in hand, in a selection process . If a similar case is found, then the system retrieves that particular case and attempts to modify it (if necessary) to produce a potential solution for the new case. The process is known as adaption .
Full Text Chapter Download: US $37.50 Add to Cart
Legal Issues for Research and Practice in Computational Forensics
The process of solving new problems by analysis of the solutions to previous problems
Full Text Chapter Download: US $37.50 Add to Cart
Only Can AI Understand Me?: Big Data Analytics, Decision Making, and Reasoning
It is a kind of experience reasoning. It is based on the principle of “similar problems have similar solutions” A case is an experienced problem and its solution. Abductive case-based reasoning is a more practical explanation-oriented reasoning paradigm.
Full Text Chapter Download: US $37.50 Add to Cart
Web 2.0 Effort Estimation
A technique that assumes that similar problems present similar solutions. It provides estimates by comparing the characteristics of the current project to be estimated against a library of historical information from completed projects with a known effort (case base).
Full Text Chapter Download: US $37.50 Add to Cart
Emotional Memory and Adaptive Personalities
Case-based reasoning (Kolodner 1993) is a reasoning architecture that stores experiences with lessons learned as cases in a case library and solves problems by retrieving the case most similar to the current situation, adapting it for reuse, and retaining new solutions once they have been applied. Case-based reasoning is also a pervasive behavior in everyday human problem solving.
Full Text Chapter Download: US $37.50 Add to Cart
Dynamic Adaptation in Ubiquitous Services: A Conceptual Architecture
A machine learning method consisting of solving a new problem according to previously solved similar problems.
Full Text Chapter Download: US $37.50 Add to Cart
Semantically Enhanced Web Service for Global Supply Chain Disruption Management
Case-based reasoning (CBR) is one of the useful mechanisms for both modeling human reasoning and building intelligent software application systems. The basic principle of case-based reasoning systems is that of solving problems by adapting the solution of similar problems solved in the past. A CBR system consists of a case base , which is the set of all cases that are known to the system. The case base can be thought of as a specific kind of knowledge base that contains only cases. When a new case is presented to the system, it checks the case base for similar cases that are most relevant to the case in hand, in a selection process . If a similar case is found, then the system retrieves that particular case and attempts to modify it (if necessary) to produce a potential solution for the new case. The process is known as adaption .
Full Text Chapter Download: US $37.50 Add to Cart
Knowledge-Based Systems
Solving new problems by adapting solutions that were previously used to solve old problem.
Full Text Chapter Download: US $37.50 Add to Cart
Evaluation of a Scenario-Based Socratic Style of Teaching and Learning Practice
Case-based reasoning (CBR) is one of the useful mechanisms for both modeling human reasoning and building intelligent software application systems. The basic principle of case-based reasoning systems is that of solving problems by adapting the solution of similar problems solved in the past. A CBR system consists of a case base , which is the set of all cases that are known to the system. The case base can be thought of as a specific kind of knowledge base that contains only cases. When a new case is presented to the system, it checks the case base for similar cases that are most relevant to the case in hand, in a selection process . If a similar case is found, then the system retrieves that particular case and attempts to modify it (if necessary) to produce a potential solution for the new case. The process is known as adaption .
Full Text Chapter Download: US $37.50 Add to Cart
Supply Chain Resilience Management Using a Semantically-Enhanced Web Service Portal
Case-based reasoning (CBR) is one of the useful mechanisms for both modeling human reasoning and building intelligent software application systems. The basic principle of case-based reasoning systems is that of solving problems by adapting the solution of similar problems solved in the past. A CBR system consists of a case base , which is the set of all cases that are known to the system. The case base can be thought of as a specific kind of knowledge base that contains only cases. When a new case is presented to the system, it checks the case base for similar cases that are most relevant to the case in hand, in a selection process . If a similar case is found, then the system retrieves that particular case and attempts to modify it (if necessary) to produce a potential solution for the new case. The process is known as adaption .
Full Text Chapter Download: US $37.50 Add to Cart
eContent Pro Discount Banner
InfoSci OnDemandECP Editorial ServicesAGOSR