scholarly journals Case-Based Reasoning Methodology for eLearning Recommendation System

2022 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Dipti D. Patil ◽  
Swati Shekapure
Keyword(s):  
Recommendation System ◽  
Case Based Reasoning ◽  
Case Based

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.

Using a Recommendation System to Support Problem Solving and Case-Based Reasoning Retrieval

2017 ◽  
Vol 23 (1) ◽  
pp. 177-187
Author(s):  
Andrew A. Tawfik ◽  
Hamed Alhoori ◽  
Charles Wayne Keene ◽  
Christian Bailey ◽  
Maureen Hogan
Keyword(s):  
Problem Solving ◽  
Recommendation System ◽  
Case Based Reasoning ◽  
Case Based

A Recommendation System for Hotel in Bali Using Case Based Reasoning Method

2021 ◽  
Vol 10 (1) ◽  
pp. 11
Author(s):  
Ni Putu Vidya Vira Prashanti ◽  
I Gede Santi Astawa
Keyword(s):  
Recommendation System ◽  
Nearest Neighbor ◽  
Case Based Reasoning ◽  
Air Conditioner ◽  
K Nearest Neighbor ◽  
Tourist Destinations ◽  
Black Box Testing ◽  
Class Room ◽  
The Right ◽  
Case Based

When on vacation, one of the essential amenities that is needed is the availability of accommodation such as hotel. One of the areas that become a holiday destination is the island of Bali. Being one of the tourist destinations of course many lodgings available in Bali with various facilities offered. The problem facing tourists is when choosing the right lodging that suits your wishes or needs, so in this study will be built a hotel recommendation system in Bali. The purpose of this research is to assist tourists in choosing the right hotel. The study used 78 hotel data sourced from the agoda.com. The methods used in this study are Case Based Reasoning and K-Nearest Neighbor.  The result of this study is that the hotel recommendation system in Bali has managed to provide hotel selection recommendations based on 14 features namely district, hotel class, room type, and availability of facilities such as breakfast, swimming pool, television, gym, air conditioner, scenery, and nightly stay price. Based on black box testing, it is obtained the result that the hotel recommendation system in Bali can function properly.   

Music Recommendation System Based on Context Using Case-Based Reasoning and Self Organizing Map

2016 ◽  
Vol 4 (2) ◽  
pp. 459
Author(s):  
Gst Ayu Vida Mastrika Giri ◽  
Agus Harjoko
Keyword(s):  
Recommendation System ◽  
Case Based Reasoning ◽  
Self Organizing Map ◽  
Music Recommendation ◽  
Indexing Method ◽  
System Output ◽  
Context Data ◽  
Music Recommendation System ◽  
Case Based ◽  
Self Organizing

Effective music recommendation can decrease listener’s effort in choosing music that will be listened. Music recommendation is not only can be obtained based on genre or audio similarity, because listener’s music choices are also influenced by the listener’s context (mood, occasion, part of day, date, weather, region, month, and weekday). This research used Case-Based Reasoning (CBR) for determining music recommendation based on listener’s context data and also Self Organizing Map (SOM) which is used as an indexing method in CBR. Inputs given by user to the system are user’s occasion and mood desired by user. The system output is a playlist consists of music that suitable with user’s context and desired mood.

Research on Multiple Cases Database Construction of Case-Based Reasoning Personalized Recommendation System

2013 ◽  
Vol 303-306 ◽  
pp. 1448-1451
Author(s):  
Jie Li Sun ◽  
Yun Lu ◽  
Fu Liang Li
Keyword(s):  
Recommendation System ◽  
Construction Method ◽  
Personalized Recommendation ◽  
Case Based Reasoning ◽  
Case Method ◽  
Database Construction ◽  
Case Based

The multiple cases database construction is one of the important links to design the personalized recommendation system. Personalized recommendation system case can be organized with multiple cases database based on expert experience and thinking patterns, combined with the traditional case method of organization. This paper studies the multiple cases database construction method of the personalized recommendation system based-CBR.

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