TY - GEN
T1 - Improving prediction quality in collaborative filtering based on clustering
AU - Kim, Taek Hun
AU - Park, Seok In
AU - Yang, Sung Bong
PY - 2008
Y1 - 2008
N2 - In this paper we present the recommender systems that use the k-means clustering method in order to solve the problems associated with neighbor selection. The first method is to solve the problem in which customers belong to different clusters due to the distance-based characteristics despite the fact that they are similar customers, by properly converting data before performing clustering. The second method explains the k-prototype algorithm performing clustering by expanding not only the numeric data but also the categorical data. The experimental results show that better prediction quality can be obtained when both methods are used together.
AB - In this paper we present the recommender systems that use the k-means clustering method in order to solve the problems associated with neighbor selection. The first method is to solve the problem in which customers belong to different clusters due to the distance-based characteristics despite the fact that they are similar customers, by properly converting data before performing clustering. The second method explains the k-prototype algorithm performing clustering by expanding not only the numeric data but also the categorical data. The experimental results show that better prediction quality can be obtained when both methods are used together.
UR - http://www.scopus.com/inward/record.url?scp=63149150198&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=63149150198&partnerID=8YFLogxK
U2 - 10.1109/WIIAT.2008.319
DO - 10.1109/WIIAT.2008.319
M3 - Conference contribution
AN - SCOPUS:63149150198
SN - 9780769534961
T3 - Proceedings - 2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008
SP - 704
EP - 710
BT - Proceedings - 2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008
T2 - 2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008
Y2 - 9 December 2008 through 12 December 2008
ER -