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SUMMARY:: Auralist: Introducing Serendipity into Music Recommendation - Da
 niele Quercia for Yuan Zhang (University of Cambridge)
DTSTART:20120426T150000Z
DTEND:20120426T160000Z
UID:TALK36719@talks.cam.ac.uk
CONTACT:Eiko Yoneki
DESCRIPTION:Recommendation systems exist to help users discover content in
  a large body of items. An ideal recommendation system should mimic the ac
 tions of a trusted friend or expert\, producing a personalised collection 
 of recommendations that balance between the desired goals of accuracy\, di
 versity\, novelty and serendipity. We introduce the Auralist recommendatio
 n framework\, a system that - in contrast to previous work\n- attempts to 
 balance and improve all four factors simultaneously.\nUsing a collection o
 f novel algorithms inspired by principles of ‘serendipitous discovery’
 \, we demonstrate a method of successfully injecting serendipity\, novelty
  and diversity into recommendations whilst limiting the impact on accuracy
 . We evaluate Auralist quantitatively over a broad set of metrics and\, wi
 th a user study on music recommendation\, show that Auralist’s emphasis 
 on serendipity indeed improves user satisfaction.\n
LOCATION:FW26\, Computer Laboratory\, William Gates Builiding
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