This site has been permanently archived. This is a static copy provided by the University of Southampton.
TY - GEN
ID - cogprints7651
UR - http://cogprints.org/7651/
A1 - De Meo, Pasquale
A1 - Ferrara, Emilio
A1 - Fiumara, Giacomo
A1 - Provetti, Alessandro
TI - Improving Recommendation Quality by Merging Collaborative Filtering and Social Relationships
Y1 - 2011///
N2 - Matrix Factorization techniques have been successfully applied to raise the quality of suggestions generated
by Collaborative Filtering Systems (CFSs). Traditional CFSs
based on Matrix Factorization operate on the ratings provided
by users and have been recently extended to incorporate
demographic aspects such as age and gender. In this paper we
propose to merge CF techniques based on Matrix Factorization
and information regarding social friendships in order to
provide users with more accurate suggestions and rankings
on items of their interest. The proposed approach has been
evaluated on a real-life online social network; the experimental
results show an improvement against existing CF approaches.
A detailed comparison with related literature is also present
AV - public
ER -