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@article{ART001042864},
author={Yong Kim and Sung Been Moon},
title={A Study on Recommendation System Using Data Mining Techniques for Large-sized Music Contents},
journal={Journal of the Korean Society for Information Management},
issn={1013-0799},
year={2007},
volume={24},
number={2},
pages={89-104},
doi={10.3743/KOSIM.2007.24.2.089}

TY - JOUR
AU - Yong Kim
AU - Sung Been Moon
TI - A Study on Recommendation System Using Data Mining Techniques for Large-sized Music Contents
JO - Journal of the Korean Society for Information Management
PY - 2007
VL - 24
IS - 2
PB - 한국정보관리학회
SP - 89
EP - 104
SN - 1013-0799
AB - This study attempts to give a personalized recommendation framework in large-sized music contents environment. Despite of many existing studies and commercial solutions for a recommendation service, large online shopping malls are still looking for a recommendation system that can serve personalized recommendation and handle large data in real-time.This research utilizes data mining technologies and new pattern matching algorithm. A clustering technique is used to get dynamic user segmentations using user preference to contents categories. Then a sequential pattern mining technique is used to extract contents access patterns in the user segmentations. Finally, the recommendation is given by our recommendation algorithm using user contents preference history and contents access patterns of the segment. In the framework, preprocessing and data transformation and transition are implemented on DBMS. The proposed system is implemented to show that the framework is feasible. In the experiment using real-world large data, personalized recommendation is given in almost real-time and shows acceptable correctness.
KW - Personalization;Recommendation system;Sequential Patterns;Clustering;Data Mining
DO - 10.3743/KOSIM.2007.24.2.089
ER -

Yong Kim and Sung Been Moon. (2007). A Study on Recommendation System Using Data Mining Techniques for Large-sized Music Contents. Journal of the Korean Society for Information Management, 24(2), 89-104.

Yong Kim and Sung Been Moon. 2007, "A Study on Recommendation System Using Data Mining Techniques for Large-sized Music Contents", Journal of the Korean Society for Information Management, vol.24, no.2 pp.89-104. Available from: doi:10.3743/KOSIM.2007.24.2.089

Yong Kim, Sung Been Moon "A Study on Recommendation System Using Data Mining Techniques for Large-sized Music Contents" Journal of the Korean Society for Information Management 24.2 pp.89-104 (2007) : 89.

Yong Kim, Sung Been Moon. A Study on Recommendation System Using Data Mining Techniques for Large-sized Music Contents. 2007; 24(2), 89-104. Available from: doi:10.3743/KOSIM.2007.24.2.089

Yong Kim and Sung Been Moon. "A Study on Recommendation System Using Data Mining Techniques for Large-sized Music Contents" Journal of the Korean Society for Information Management 24, no.2 (2007) : 89-104.doi: 10.3743/KOSIM.2007.24.2.089

Yong Kim; Sung Been Moon. A Study on Recommendation System Using Data Mining Techniques for Large-sized Music Contents. Journal of the Korean Society for Information Management, 24(2), 89-104. doi: 10.3743/KOSIM.2007.24.2.089

Yong Kim; Sung Been Moon. A Study on Recommendation System Using Data Mining Techniques for Large-sized Music Contents. Journal of the Korean Society for Information Management. 2007; 24(2) 89-104. doi: 10.3743/KOSIM.2007.24.2.089

Yong Kim, Sung Been Moon. A Study on Recommendation System Using Data Mining Techniques for Large-sized Music Contents. 2007; 24(2), 89-104. Available from: doi:10.3743/KOSIM.2007.24.2.089

Yong Kim and Sung Been Moon. "A Study on Recommendation System Using Data Mining Techniques for Large-sized Music Contents" Journal of the Korean Society for Information Management 24, no.2 (2007) : 89-104.doi: 10.3743/KOSIM.2007.24.2.089