MOVIE RECOMMENDATION WITH K-MEANS CLUSTERING AND SELF-ORGANIZING MAP METHODS

Eugene Seo, Ho-Jin Choi

2010

Abstract

Recommendation System has been developed to offer users a personalized service. We apply K-means and Self-Organizing Map (SOM) methods for the recommendation system. We explain each method in movie recommendation, and compare their performance in the sense of prediction accuracy and learning time. Our experimental results with given Netflix movie datasets demonstrates how SOM performs better than K-means to give precise prediction of movie recommendation with discussion, but it needs to be solved for the overall time of computation.

Paper Citation

in Harvard Style

Seo E. and Choi H. (2010). MOVIE RECOMMENDATION WITH K-MEANS CLUSTERING AND SELF-ORGANIZING MAP METHODS . In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-674-021-4, pages 385-390. DOI: 10.5220/0002737603850390

in Bibtex Style

@conference{icaart10,
author={Eugene Seo and Ho-Jin Choi},
title={MOVIE RECOMMENDATION WITH K-MEANS CLUSTERING AND SELF-ORGANIZING MAP METHODS},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2010},
pages={385-390},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002737603850390},
isbn={978-989-674-021-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - MOVIE RECOMMENDATION WITH K-MEANS CLUSTERING AND SELF-ORGANIZING MAP METHODS
SN - 978-989-674-021-4
AU - Seo E.
AU - Choi H.
PY - 2010
SP - 385
EP - 390
DO - 10.5220/0002737603850390