scholarly journals Design and Implementation of personalized recommendation system using Case-based Reasoning Technique

2002 ◽  
Vol 9D (6) ◽  
pp. 1009-1016 ◽  
Keyword(s):  
Recommendation System ◽  
Personalized Recommendation ◽  
Case Based Reasoning ◽  
Design And Implementation ◽  
Reasoning Technique ◽  
Case Based

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.

Study on the Key Technology of Personalized Recommendation of Case-Based Reasoning

2013 ◽  
Vol 380-384 ◽  
pp. 2271-2275
Author(s):  
Fu Liang Li ◽  
Yan Feng Bai ◽  
Jie Li Sun
Keyword(s):  
Recommendation System ◽  
Personalized Recommendation ◽  
Case Based Reasoning ◽  
Key Technology ◽  
Case Based

The key technology of personalized recommendation based on CBR involves the representation and the organization of case, construction and maintenance of multiple cases library, judging of the similarity of case and methods of retrieval, and the combination of personalized recommendation technology. The four interrelated aspects are the important links to design the personalized recommendation system. This paper studies the key technology of the personalized recommendation system based on CBR.

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.

Sign in / Sign up

Export Citation Format

Share Document