TY - GEN
T1 - Enhancing service site selection via joint learning
AU - Junjie, Wu
AU - Heng, Wang
AU - Le, Zhang
AU - Jian, Chen
PY - 2009
Y1 - 2009
N2 - Given its importance, the problem of selecting the appropriate site for a service business has attracted great attentions in the literature. However, to quantify the relationships between the target site and its nearby businesses is still a challenging task. To this end, in this paper, we propose a novel joint learning scheme for service site selections. A case study for bank branch selections is also provided to demonstrate the usefulness of our scheme.
AB - Given its importance, the problem of selecting the appropriate site for a service business has attracted great attentions in the literature. However, to quantify the relationships between the target site and its nearby businesses is still a challenging task. To this end, in this paper, we propose a novel joint learning scheme for service site selections. A case study for bank branch selections is also provided to demonstrate the usefulness of our scheme.
UR - https://www.scopus.com/pages/publications/61649117984
U2 - 10.1109/AMIGE.2008.ECP.44
DO - 10.1109/AMIGE.2008.ECP.44
M3 - 会议稿件
AN - SCOPUS:61649117984
SN - 9781424429721
T3 - 2008 IEEE Symposium on Advanced Management of Information for Globalized Enterprises, AMIGE 2008 - Proceedings
SP - 181
EP - 185
BT - 2008 IEEE Symposium on Advanced Management of Information for Globalized Enterprises, AMIGE 2008 - Proceedings
T2 - 2008 IEEE Symposium on Advanced Management of Information for Globalized Enterprises, AMIGE 2008
Y2 - 28 September 2008 through 29 September 2008
ER -