A Collaborative Filtering System Using Clustering and Genetic Algorithms

  • Soojung LeeEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1071)


Recommender systems have been essential these days to assist online customers to acquire useful information. However, one of the popular types of the systems called memory-based collaborative filtering suffers from several fundamental problems in spite of its main advantages such as simplicity and efficiency. This study addresses the scalability problem which is one of major problems of the system. We employ a clustering technique to handle the problem and propose a novel idea using the genetic algorithm to enhance the performance of the system in terms of prediction accuracy, not to mention scalability. Experimental results demonstrated successful performance achievements of the proposed method under various data conditions.


Collaborative filtering Recommender system Clustering Genetic algorithm 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Gyeongin National University of EducationAnyangRepublic of Korea

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