Developing Knowledge Based Recommender System for Tourist Attraction Area Selection in Ethiopia: A Case Based Reasoning Approach

In this paper, a knowledge service method that supports the intelligent design of products is investigated. The proposed method provides the solutions to computational problems and reasoning and decision-making problems in the field of intelligent design. The requirement analysis of a knowledge-based intelligent design system integrates design knowledge into case-based reasoning activities through scheme analysis, scheme evaluation, and scheme adjustment, thus achieving knowledge-based intelligent reasoning and decision-making. During the similarity matching, a new hybrid similarity measurement method is proposed to calculate the similarity of crisp and fuzzy sets. This method integrates the fuzzy set similarity theory based on the traditional similarity measurement method. A method of attribute level classification is proposed to assign weight coefficients. The attributes are divided into the primary matching and auxiliary matching levels according to the decisiveness of case matching, and the set of weight coefficients is continuously and dynamically updated through case-based reasoning learning. Then, the weighted global similarity measure is used to obtain the set of similar cases from the case database. Finally, a design example of a computer numerical control tool holder product is studied to present the practicability and effectiveness of the proposed method.

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Implementasi Metode Case Based Reasoning Untuk Mendeteksi Kerusakan Televisi

JURNAL MEDIA INFORMATIKA BUDIDARMA ◽

10.30865/mib.v5i2.2952 ◽

2021 ◽

Vol 5 (2) ◽

pp. 624

Author(s):

Sursih Wulandari ◽

Marnis Nasution ◽

Mustafa Haris Munandar

Keyword(s):

High Weight ◽

Study Data ◽

Design System ◽

Case Based Reasoning ◽

Collection System ◽

Literature Study ◽

Knowledge Based ◽

Testing Case ◽

Case Based ◽

System Program

The process of deteriorating television should indeed be done by an expert who is a television expert himself, but because television is a tool that is no longer common for people to know him, many people also have television in their respective homes. Even for television repairs, it is quite expensive, so some people who have televisions can do television maintenance at home. The lack of knowledge possessed by the community can lead to wrong handling of television maintenance / maintenance and this has a fatal impact. Hopefully the existence of this system can help the community in diagnosing the damage to their televisions. In that case they need not bother to call for repairmen or bring in a television repair shop. Here the authors provide solutions to solve the problems that often arise on television. In this study, it discusses how to care for television officers. The research objective is to analyze a desktop-based expert system program that contains the knowledge of an expert / doctor whose truth is believed to have the ability to be able to diagnose the disease from the symptoms of damage that has been damaged by television damage quickly and precisely. The stages of research carried out in this study include literature study, data collection, system design, system creation, system testing. Case Based Reasoning is a method used to build a knowledge-based system. The source of system knowledge is obtained by collecting the handling of cases by an expert / expert. Therefore, many problems in television damage are usually due to the negligence of the television owner himself. The first step in solving a problem is by first identifying the scope of the problem to be resolved, this also applies to any Artificial Intelligence (AI) programming. The results obtained in the study for the diagnosis of conjunctivitis were the value of old cases and new cases which obtained a high weight value, namely 1 from the third case

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A case-based reasoning recommender system for sustainable smart city development

AI & Society ◽

10.1007/s00146-020-00984-2 ◽

2020 ◽

Cited By ~ 1

Author(s):

Bokolo Anthony Jnr

Keyword(s):

Recommender System ◽

Smart City ◽

Case Based Reasoning ◽

City Development ◽

Case Based

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Knowledge-Based Systems

Encyclopedia of Artificial Intelligence ◽

10.4018/978-1-59904-849-9.ch146 ◽

2011 ◽

pp. 989-995 ◽

Cited By ~ 1

Author(s):

Adrian A. Hopgood

Keyword(s):

Computational Intelligence ◽

Early Research ◽

Computer Hardware ◽

Case Based Reasoning ◽

Major Theme ◽

Knowledge Based Systems ◽

Rule Based ◽

Knowledge Based ◽

Explicit Representations ◽

Case Based

The tools of artificial intelligence (AI) can be divided into two broad types: knowledge-based systems (KBSs) and computational intelligence (CI). KBSs use explicit representations of knowledge in the form of words and symbols. This explicit representation makes the knowledge more easily read and understood by a human than the numerically derived implicit models in computational intelligence. KBSs include techniques such as rule-based, modelbased, and case-based reasoning. They were among the first forms of investigation into AI and remain a major theme. Early research focused on specialist applications in areas such as chemistry, medicine, and computer hardware. These early successes generated great optimism in AI, but more broad-based representations of human intelligence have remained difficult to achieve (Hopgood, 2003; Hopgood, 2005).

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