Earticle

초록

영어

Collaborative filtering is a representative technique of a recommendation system. Collaborative filtering is a method of determining a recommendation target based on similarity between users or items. Distributed parallel collaborative filtering was proposed to speed up the computational speed of collaborative filtering. However, the data skewness problem caused by imbalanced data distribution still remains. Therefore, in this study, we proposed a data distribution and processing method based on the user taste repertoire analysis method to solve the data skewness problem caused by data distribution imbalance. So, the repertorie analysis is to analyze the range and number of areas of the services previously used by the users. In the proposed method, data is distributed based on the results of the repertorie analysis of the services previously used by the users. Our experiment distributing data of users based on the results of the repertoire analysis. It was shown that the performance was sufficiently usable as measuring RMSE and execution time.

목차

Abstract
1. Introduction
2. Related Works
3. Methods
4. Experiments
5. Conclusions
Acknowledgements
References

키워드

저자

• Choelhan Moon [ Computer Science and Engineering, KOREATECH Cheonan, South Korea ]
• Seongjun Choe [ Computer Science and Engineering, KOREATECH Cheonan, South Korea ]
• Han Ki Son [ Computer Science and Engineering, KOREATECH Cheonan, South Korea ]
• Jun-Ki Min [ Computer Science and Engineering, KOREATECH Cheonan, South Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국차세대컴퓨팅학회 학술대회

• 간기

  반년간

• 수록기간

  2021~2025

• 십진분류

  KDC 566 DDC 004