하이브리드 협업 필터링 알고리즘에 관한 연구

Collaborative filtering algorithms are the most successful and popular technologies used for product recommendation to date and is used in many of the most successful recommender systems on the Web. In this paper, we modify the current collaborative filtering algorithm to improve the performance of its recommendations and propose a hybrid collaborative filtering algorithm wihich considers not only the similarity between customers but also the similarity between products purchased. Also we proposed and experimented a new filtering technique which could be demonstrated a better accuracy. The new filtering technique is Hybrid Collaborative Filtering which will enable efficient product selection in the internet shopping-mall.