TY - GEN
T1 - An effective threshold-based neighbor selection in collaborative filtering
AU - Kim, Tack Hun
AU - Yang, Sung Bong
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2007
Y1 - 2007
N2 - In this paper we present a recommender system using an effective threshold-based neighbor selection in collaborative filtering. The proposed method uses the substitute neighbors of the test customer who may have an unusual preferences or who are the first rater. The experimental results show that the recommender systems using the proposed method find the proper neighbors and give a good prediction quality.
AB - In this paper we present a recommender system using an effective threshold-based neighbor selection in collaborative filtering. The proposed method uses the substitute neighbors of the test customer who may have an unusual preferences or who are the first rater. The experimental results show that the recommender systems using the proposed method find the proper neighbors and give a good prediction quality.
UR - http://www.scopus.com/inward/record.url?scp=37149046877&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=37149046877&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-71496-5_75
DO - 10.1007/978-3-540-71496-5_75
M3 - Conference contribution
AN - SCOPUS:37149046877
SN - 3540714944
SN - 9783540714941
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 712
EP - 715
BT - Advances in Information Retrieval - 29th European Conference on IR Research, ECIR 2007, Proceedings
PB - Springer Verlag
T2 - 29th European Conference on IR Research, ECIR 2007
Y2 - 2 April 2007 through 5 April 2007
ER -