A study of development for movie recommendation system algorithm using filtering
필터링기법을 이용한 영화 추천시스템 알고리즘 개발에 관한 연구

Sun Ok Kim, Soo Yong Lee, Seok Jun Lee, Hee Choon Lee, Seon Su Ji
2013 Journal of the Korean Data and Information Science Society  
The purchase of items in e-commerce is a little bit different from that of items in off-line. The recommendation of items in off-line is conducted by salespersons' recommendation, However, the item recommendation in e-commerce cannot be recommended by salespersons, and so different types of methods can be recommended in e-commerce. Recommender system is a method which recommends items in e-commerce. Preferences of customers who want to purchase new items can be predicted by the preferences of
more » ... he preferences of customers purchasing existing items. In the recommender system, the items with estimated high preferences can be recommended to customers. The algorithm of collaborative filtering is used in recommender system of e-commerce, and the list of recommended items is made by estimated values, and then the list is recommended to customers. The dataset used in this research are 100k dataset and 1 million dataset in Movielens dataset. Similar results in two dataset are deducted for generalization. To suggest a new algorithm, distribution features of estimated values are analyzed by the existing algorithm and transformed algorithm. In addition, respondent'distribution features are analyzed respectively. To improve the collaborative filtering algorithm in neighborhood recommender system, a new algorithm method is suggested on the basis of existing algorithm and transformed algorithm.
doi:10.7465/jkdi.2013.24.4.803 fatcat:hfe5etai7zap7a63tuclhxqoje