---
abstract: "Matrix Factorization techniques have been successfully applied to raise the quality of suggestions generated\r\nby Collaborative Filtering Systems (CFSs). Traditional CFSs\r\nbased on Matrix Factorization operate on the ratings provided\r\nby users and have been recently extended to incorporate\r\ndemographic aspects such as age and gender. In this paper we\r\npropose to merge CF techniques based on Matrix Factorization\r\nand information regarding social friendships in order to\r\nprovide users with more accurate suggestions and rankings\r\non items of their interest. The proposed approach has been\r\nevaluated on a real-life online social network; the experimental\r\nresults show an improvement against existing CF approaches.\r\nA detailed comparison with related literature is also present"
altloc: []
chapter: ~
commentary: ~
commref: ~
confdates: ~
conference: "ISDA '11: 11th International Conference on Intelligent Systems Design and Applications"
confloc: ~
contact_email: ~
creators_id: []
creators_name:
  - family: De Meo
    given: Pasquale
    honourific: ''
    lineage: ''
  - family: Ferrara
    given: Emilio
    honourific: ''
    lineage: ''
  - family: Fiumara
    given: Giacomo
    honourific: ''
    lineage: ''
  - family: Provetti
    given: Alessandro
    honourific: ''
    lineage: ''
date: 2011
date_type: published
datestamp: 2011-10-01 00:34:40
department: ~
dir: disk0/00/00/76/51
edit_lock_since: ~
edit_lock_until: 0
edit_lock_user: ~
editors_id: []
editors_name: []
eprint_status: archive
eprintid: 7651
fileinfo: application/pdf;http://cogprints.org/7651/1/isda2011%2Drec%2Dsys.pdf
full_text_status: public
importid: ~
institution: ~
isbn: ~
ispublished: pub
issn: ~
item_issues_comment: []
item_issues_count: ~
item_issues_description: []
item_issues_id: []
item_issues_reported_by: []
item_issues_resolved_by: []
item_issues_status: []
item_issues_timestamp: []
item_issues_type: []
keywords: ~
lastmod: 2011-10-01 00:34:40
latitude: ~
longitude: ~
metadata_visibility: show
note: ~
number: ~
pagerange: ~
pubdom: TRUE
publication: ~
publisher: ~
refereed: TRUE
referencetext: ~
relation_type: []
relation_uri: []
reportno: ~
rev_number: 10
series: ~
source: ~
status_changed: 2011-10-01 00:34:40
subjects:
  - comp-sci-art-intel
succeeds: ~
suggestions: ~
sword_depositor: ~
sword_slug: ~
thesistype: ~
title: Improving Recommendation Quality by Merging Collaborative Filtering and Social Relationships
type: confpaper
userid: 14714
volume: ~
<script src="//archive-bar.soton.ac.uk/archive-bar.js"></script>