TY - GEN
T1 - Opinion leader based filtering
AU - Cheon, Hyeonjae
AU - Lee, Hongchul
PY - 2005
Y1 - 2005
N2 - Recommendation systems are helping users find the information, products, and other people they most want to find, therefore many on-line stores provide recommending services e.g. Amazon, CDNOW, etc. Most recommendation systems use collaborative filtering, content-based filtering, and hybrid techniques to predict user preferences. We discuss the strengths and weaknesses of the techniques and present a unique recommendation system that automatically selects opinion leaders by category or genre to improve the performance of recommendation. Finally, our approach will help to solve the cold-start problem in collaborative filtering.
AB - Recommendation systems are helping users find the information, products, and other people they most want to find, therefore many on-line stores provide recommending services e.g. Amazon, CDNOW, etc. Most recommendation systems use collaborative filtering, content-based filtering, and hybrid techniques to predict user preferences. We discuss the strengths and weaknesses of the techniques and present a unique recommendation system that automatically selects opinion leaders by category or genre to improve the performance of recommendation. Finally, our approach will help to solve the cold-start problem in collaborative filtering.
UR - http://www.scopus.com/inward/record.url?scp=33744899095&partnerID=8YFLogxK
U2 - 10.1007/11599517_40
DO - 10.1007/11599517_40
M3 - Conference contribution
AN - SCOPUS:33744899095
SN - 3540308504
SN - 9783540308508
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 352
EP - 359
BT - Digital Libraries
T2 - 8th International Conference on Asian Digital Libraries, ICADL 2005
Y2 - 12 December 2005 through 15 December 2005
ER -