TY - GEN
T1 - MobHinter
T2 - 2008 2nd ACM International Conference on Recommender Systems, RecSys'08
AU - Schifanella, Rossano
AU - Panisson, Andŕ
AU - Gena, Cristina
AU - Ruffo, Giancarlo
PY - 2008
Y1 - 2008
N2 - We focus on collaborative filtering dealing with self-organizing communities, host mobility, wireless access, and ad-hoc communications. In such a domain, knowledge representation and users profiling can be hard; remote servers can be often unreachable due to client mobility; and feedback ratings collected during random connections to other users' adhoc devices can be useless, because of natural differences between human beings. Our approach is based on so called Affinity Networks, and on a novel system, called MobHinter, that epidemically spreads recommendations through spontaneous similarities between users. Main results of our study are two fold: firstly, we show how to reach comparable recommendation accuracies in the mobile domain as well as in a complete knowledge scenario; secondly, we propose epidemic collaborative strategies that can reduce rapidly and realistically the cold start problem.
AB - We focus on collaborative filtering dealing with self-organizing communities, host mobility, wireless access, and ad-hoc communications. In such a domain, knowledge representation and users profiling can be hard; remote servers can be often unreachable due to client mobility; and feedback ratings collected during random connections to other users' adhoc devices can be useless, because of natural differences between human beings. Our approach is based on so called Affinity Networks, and on a novel system, called MobHinter, that epidemically spreads recommendations through spontaneous similarities between users. Main results of our study are two fold: firstly, we show how to reach comparable recommendation accuracies in the mobile domain as well as in a complete knowledge scenario; secondly, we propose epidemic collaborative strategies that can reduce rapidly and realistically the cold start problem.
KW - Ad-hoc networks
KW - Recommender systems
KW - Social collaborative filtering
UR - http://www.scopus.com/inward/record.url?scp=62149141554&partnerID=8YFLogxK
U2 - 10.1145/1454008.1454014
DO - 10.1145/1454008.1454014
M3 - Conference contribution
AN - SCOPUS:62149141554
SN - 9781605580937
T3 - RecSys'08: Proceedings of the 2008 ACM Conference on Recommender Systems
SP - 27
EP - 34
BT - RecSys'08
Y2 - 23 October 2008 through 25 October 2008
ER -