TY - JOUR
T1 - Hybrid recommendation approaches
T2 - 38th Annual Hawaii International Conference on System Sciences
AU - Shih, Ya Yueh
AU - Liu, Duen-Ren
PY - 2005/11/10
Y1 - 2005/11/10
N2 - Collaborative filtering (CF) method has been successfully used in recommender systems to support product recommendation, but it has several limitations. This work uses customer demands derived from the frequent purchased products in each industry as valuable content information. Accordingly, this work explores two hybrid approaches each of which combines CF and customer demands to improve quality of recommendation. Valuable content information is also included as a factor in making recommendations for re-ranking candidate products. The experimental results indicate that the quality of recommendation obtained by the combined methods is promising.
AB - Collaborative filtering (CF) method has been successfully used in recommender systems to support product recommendation, but it has several limitations. This work uses customer demands derived from the frequent purchased products in each industry as valuable content information. Accordingly, this work explores two hybrid approaches each of which combines CF and customer demands to improve quality of recommendation. Valuable content information is also included as a factor in making recommendations for re-ranking candidate products. The experimental results indicate that the quality of recommendation obtained by the combined methods is promising.
UR - http://www.scopus.com/inward/record.url?scp=27544474814&partnerID=8YFLogxK
U2 - 10.1109/HICSS.2005.302
DO - 10.1109/HICSS.2005.302
M3 - Conference article
AN - SCOPUS:27544474814
SN - 1530-1605
JO - Proceedings of the Annual Hawaii International Conference on System Sciences
JF - Proceedings of the Annual Hawaii International Conference on System Sciences
Y2 - 3 January 2005 through 6 January 2005
ER -