scholarly journals Retrieval, reuse, revision and retention in case-based reasoning

2005 ◽  
Vol 20 (3) ◽  
pp. 215-240 ◽  
Author(s):  
RAMON LOPEZ DE MANTARAS ◽  
DAVID MCSHERRY ◽  
DEREK BRIDGE ◽  
DAVID LEAKE ◽  
BARRY SMYTH ◽  
...  
Keyword(s):  
Problem Solving ◽  
Analogical Reasoning ◽  
Case Based Reasoning ◽  
The Past ◽  
Future Problem ◽  
Considerable Success ◽  
Representative Selection ◽  
Case Based ◽  
Selection Of

Case-based reasoning (CBR) is an approach to problem solving that emphasizes the role of prior experience during future problem solving (i.e., new problems are solved by reusing and if necessary adapting the solutions to similar problems that were solved in the past). It has enjoyed considerable success in a wide variety of problem solving tasks and domains. Following a brief overview of the traditional problem-solving cycle in CBR, we examine the cognitive science foundations of CBR and its relationship to analogical reasoning. We then review a representative selection of CBR research in the past few decades on aspects of retrieval, reuse, revision and retention.

A Case Based Reasoning System For Recommendation Of Restaurant In Jimbaran Using K-Nearest Neighbor

2020 ◽  
Vol 9 (2) ◽  
pp. 267
Author(s):  
I Gede Teguh Mahardika ◽  
I Wayan Supriana
Keyword(s):  
Recommendation System ◽  
Nearest Neighbor ◽  
Case Based Reasoning ◽  
Retrieval Process ◽  
K Nearest Neighbor ◽  
Reasoning System ◽  
Human Ability ◽  
And Function ◽  
Case Based ◽  
Selection Of

Culinary is one of the favorite businesses today. The number of considerations to choose a restaurant or place to visit becomes one of the factors that is difficult to determine the restaurant or place to eat. To get the desired place to eat advice, one needs a recommendation system. Decisions made by the recommendation system can be used as a reference to determine the choice of restaurants. One method that can be used to build a recommendation system is Case Based Reasoning. The Case Based Reasoning (CBR) method mimics human ability to solve a problem or cases. The retrieval process is the most important stage, because at this stage the search for a solution for a new case is carried out. The study used the K-Nearest Neighbor method to find closeness between new cases and case bases. With the selection of features used as domains in the system, the results of recommendations presented can be more suggestive and accurate. The system successfully provides complex recommendations based on the type and type of food entered by the user. Based on blackbox testing, the system has features that can be used and function properly according to the purpose of creating the system.

scholarly journals Indestructible Pasts and Paranoid Presents: John Franzen against Active Forgetting in Purity

2019 ◽  
pp. 21-34
Author(s):  
Cristina Garrigós
Keyword(s):  
Traumatic Event ◽  
The Novel ◽  
Contemporary Society ◽  
The Public ◽  
The Past ◽  
Personal Archives ◽  
Conscious Process ◽  
Unconscious Desire ◽  
Selection Of

Forgetting and remembering are as inevitably linked as lifeand death. Sometimes, forgetting is motivated by a biological disorder, brain damage, or it is the product of an unconscious desire derived from a traumatic event (psychological repression). But in some cases, we can motivate forgetting consciously (thought suppression). It is through the conscious repression of memories that we can find self-preservation and move forward, although this means that we create a fable of our lives, as Nietzsche says in his essay “On the Uses and Disadvantages of History for Life” (1997). In Jonathan Franzen’s novel, Purity (2015), forgetting is an active and conscious process by which the characters choose to forget certain episodes of their lives to be able to construct new identities. The erased memories include murder, economical privileges derived from illegal or unethical commercial processes, or dark sexual episodes. The obsession with forgetting the past links the lives of the main characters, and structures the narrative of the novel. The motivated erasure of memories becomes, thus, a way that the characters have to survive and face the present according to a (fake) narrative that they have constructed. But is motivated forgetting possible? Can one completely suppress facts in an active way? This paper analyses the role of forgetting in Franzen’s novel in relation to the need in our contemporary society to deny, hide, or erase uncomfortable data from our historical or personal archives; the need to make disappear stories which we do not want to accept, recognize, and much less make known to the public. This is related to how we manage information in the age of technology, the “selection” of what is to be the official story, and how we rewrite our own history

A Blackboard Architecture to Support Case-Based Reasoning in Mechanical Design

1992 ◽  
Author(s):  
Theodore Bardsz ◽  
Ibrahim Zeid
Keyword(s):  
Problem Solving ◽  
Engineering Design ◽  
Mechanical Design ◽  
Maximum Amount ◽  
Design Solution ◽  
Case Based Reasoning ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Design Plan ◽  
Case Based

Abstract One of the most significant issues in applying case-based reasoning (CBR) to mechanical design is to integrate previously unrelated design plans towards the solution of a new design problem. The total design solution (the design plan structure) can be composed of both retrieved and dynamically generated design plans. The retrieved design plans must be mapped to fit the new design context, and the entire design plan structure must be evaluated. An architecture utilizing opportunistic problem solving in a blackboard environment is used to map and evaluate the design plan structure effectively and successfuly. The architecture has several assets when integrated into a CBR environment. First, the maximum amount of information related to the design is generated before any of the mapping problems are addressed. Second, mapping is preformed as just another action toward the evaluation of the design plan. Lastly, the architecture supports the inclusion of memory elements from the knowledge base in the design plan structure. The architecture is implemented using the GBB system. The architecture is part of a newly developed CBR System called DEJAVU. The paper describes DEJAVU and the architecture. An example is also included to illustrate the use of DEJAVU to solve engineering design problems.

Case-Based Reasoning and Some Typical Applications

2014 ◽  
pp. 229-267 ◽  
Author(s):  
Durga Prasad Roy ◽  
Baisakhi Chakraborty
Keyword(s):  
Problem Solving ◽  
Machine Intelligence ◽  
Case Based Reasoning ◽  
Engineering System ◽  
Yale University ◽  
Control Pattern ◽  
Clustering And Classification ◽  
How People Learn ◽  
Case Based

Case-Based Reasoning (CBR) arose out of research into cognitive science, most prominently that of Roger Schank and his students at Yale University, during the period 1977–1993. CBR may be defined as a model of reasoning that incorporates problem solving, understanding, and learning, and integrates all of them with memory processes. It focuses on the human problem solving approach such as how people learn new skills and generates solutions about new situations based on their past experience. Similar mechanisms to humans who intelligently adapt their experience for learning, CBR replicates the processes by considering experiences as a set of old cases and problems to be solved as new cases. To arrive at the conclusions, it uses four types of processes, which are retrieve, reuse, revise, and retain. These processes involve some basic tasks such as clustering and classification of cases, case selection and generation, case indexing and learning, measuring case similarity, case retrieval and inference, reasoning, rule adaptation, and mining to generate the solutions. This chapter provides the basic idea of case-based reasoning and a few typical applications. The chapter, which is unique in character, will be useful to researchers in computer science, electrical engineering, system science, and information technology. Researchers and practitioners in industry and R&D laboratories working in such fields as system design, control, pattern recognition, data mining, vision, and machine intelligence will benefit.

Fifty years ago: ‘The scope of occupational medicine in a university health service’

2020 ◽  
pp. 202-203
Author(s):  
Anthony Ryle
Keyword(s):  
Health Service ◽  
Physical Health ◽  
Occupational Medicine ◽  
Potential Role ◽  
Health And Safety ◽  
Academic Achievements ◽  
The Past ◽  
Selection Of

This series provides a selection of articles from the past. In Fifty years ago: The scope of occupational medicine in a university health service Anthony Ryle briefly explores the potential role of a University Health Service in relation to students’ academic achievements and failures, rather than their physical health and safety.

A Case-Based Reasoning Approach for the Cybersecurity Incident Recording and Resolution

2019 ◽  
Vol 29 (11n12) ◽  
pp. 1607-1627
Author(s):  
Raul Ceretta Nunes ◽  
Marcelo Colomé ◽  
Fabio André Barcelos ◽  
Marcelo Garbin ◽  
Gustavo Bathu Paulus ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Problem Solving ◽  
Case Based Reasoning ◽  
Intelligent Computing ◽  
Resolution System ◽  
Concrete Problem ◽  
Different Types ◽  
Practice Knowledge ◽  
Resolution Data ◽  
Case Based

Intelligent computing techniques have a paramount importance to the treatment of cybersecurity incidents. In such Artificial Intelligence (AI) context, while most of the algorithms explored in the cybersecurity domain aim to present solutions to intrusion detection problems, these algorithms seldom approach the correction procedures that are explored in the resolution of cybersecurity incident problems that already took place. In practice, knowledge regarding cybersecurity resolution data and procedures is being under-used in the development of intelligent cybersecurity systems, sometimes even lost and not used at all. In this context, this work proposes the Case-based Cybersecurity Incident Resolution System (CCIRS), a system that implements an approach to integrate case-based reasoning (CBR) techniques and the IODEF standard in order to retain concrete problem-solving experiences of cybersecurity incident resolution to be reused in the resolution of new incidents. Different types of experimental results so far obtained with the CCIRS show that information security knowledge can be retained with our approach in a reusable memory improving the resolution of new cybersecurity problems.

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