scholarly journals Decision Classification Enhances Case-Based Reasoning

2011 ◽  
Vol 1 (4) ◽  
Author(s):  
Stephen L. Woehrle
Keyword(s):  
Decision Making ◽  
Classification Scheme ◽  
Case Based Reasoning ◽  
Different Types ◽  
Descriptive Framework ◽  
Case Based

In order to arrive at a meaningful and useful classification of decisions, a sufficiently descriptive framework for classification should be created. The use of the traditional programmed-nonprogrammed dichotomy is acceptable, but decisions themselves cannot always be treated as a single either/or entity. Decision-making is a process involving distinct and separable steps. A programmed-nonprogrammed classification scheme will be applied to a variety of different types of decisions. Using Case-based Reasoning (CBR) various decision scenarios with their corresponding classifications can be stored. The resulting database is a growing and evolving body of experience and knowledge to be used for future decision-making.

scholarly journals Towards Transparent Human-in-the-Loop Classification of Fraudulent Web Shops

2020 ◽  
Author(s):  
Daphne Odekerken ◽  
Floris Bex
Keyword(s):  
Case Based Reasoning ◽  
Agent Architecture ◽  
Human In The Loop ◽  
Levels Of Detail ◽  
Legal Case ◽  
Dynamic Argumentation ◽  
Case Based

We propose an agent architecture for transparent human-in-the-loop classification. By combining dynamic argumentation with legal case-based reasoning, we create an agent that is able to explain its decisions at various levels of detail and adapts to new situations. It keeps the human analyst in the loop by presenting suggestions for corrections that may change the factors on which the current decision is based and by enabling the analyst to add new factors. We are currently implementing the agent for classification of fraudulent web shops at the Dutch Police.

scholarly journals Wear Debris Classification of Steel Production Equipment using Feature Fusion and Case-based Reasoning

2018 ◽  
Vol 58 (7) ◽  
pp. 1293-1299 ◽  
Author(s):  
Hongbing Wang ◽  
Rong Huang ◽  
Liyuan Gao ◽  
Weishen Wang ◽  
Anjun Xu ◽  
...  
Keyword(s):  
Wear Debris ◽  
Feature Fusion ◽  
Steel Production ◽  
Production Equipment ◽  
Case Based Reasoning ◽  
Case Based

Intelligent Classification of Palm Oil Tree Pollination Using E-Nose

Mekatronika ◽  
2020 ◽  
Vol 2 (1) ◽  
pp. 28-37
Author(s):  
Abdul Rahim Jalil ◽  
Muhammad Sharfi Najib ◽  
Suhaimi Mohd Daud ◽  
Mujahid Mohamad
Keyword(s):  
Palm Oil ◽  
Case Based Reasoning ◽  
Artificial Intelligent ◽  
Male And Female ◽  
Intelligent Technique ◽  
Insect Activity ◽  
Artificial Intelligent Technique ◽  
Case Based ◽  
Odour Profile

The pollination period is one of the crucial steps needed to ensure crop yield increases, especially in palm oil palm plantations. Most of the research has difficulty determining the pollination period of palm oil. Many problems contribute to this problem, such as difficut to reach and depedency of the polination insect as the insect activity is influenced by the surrounding enviroment.E-Nose can help determine the period by classifiy odour pattern of the male and female palm oil flower. The pattern of each of the flowers were classified using cased – based reasoning artificial intelligent technique. This paper shows the research of the palm oil pollination flower odour profile pattern using case-based reasoning (CBR) classifier.

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.

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.

A case-based reasoning system for fault detection and isolation: a case study on complex gearboxes

2019 ◽  
Vol 25 (2) ◽  
pp. 213-235 ◽  
Author(s):  
Soumava Boral ◽  
Sanjay Kumar Chaturvedi ◽  
V.N.A. Naikan
Keyword(s):  
Decision Making ◽  
Fault Detection ◽  
Large Scale ◽  
Fault Detection And Isolation ◽  
Decision Making Process ◽  
Case Based Reasoning ◽  
Content Type ◽  
Complex Decision Making ◽  
Complex Decision ◽  
Case Based

Purpose Usually, the machinery in process plants is exposed to harsh and uncontrolled environmental conditions. Even after taking different types of preventive measures to detect and isolate the faults at the earliest possible opportunity becomes a complex decision-making process that often requires experts’ opinions and judicious decisions. The purpose of this paper is to propose a framework to detect, isolate and to suggest appropriate maintenance tasks for large-scale complex machinery (i.e. gearboxes of steel processing plant) in a simplified and structured manner by utilizing the prior fault histories available with the organization in conjunction with case-based reasoning (CBR) approach. It is also demonstrated that the proposed framework can easily be implemented by using today’s graphical user interface enabled tools such as Microsoft Visual Basic and similar. Design/methodology/approach CBR, an amalgamated domain of artificial intelligence and human cognitive process, has been applied to carry out the task of fault detection and isolation (FDI). Findings The equipment failure history and actions taken along with the pertinent health indicators are sufficient to detect and isolate the existing fault(s) and to suggest proper maintenance actions to minimize associated losses. The complex decision-making process of maintaining such equipment can exploit the principle of CBR and overcome the limitations of the techniques such as artificial neural networks and expert systems. The proposed CBR-based framework is able to provide inference with minimum or even with some missing information to take appropriate actions. This proposed framework would alleviate from the frequent requirement of expert’s interventions and in-depth knowledge of various analysis techniques expected to be known to process engineers. Originality/value The CBR approach has demonstrated its usefulness in many areas of practical applications. The authors perceive its application potentiality to FDI with suggested maintenance actions to alleviate an end-user from the frequent requirement of an expert for diagnosis or inference. The proposed framework can serve as a useful tool/aid to the process engineers to detect and isolate the fault of large-scale complex machinery with suggested actions in a simplified way.

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