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» Item Preference Parameters from Grouped Ranking Observations
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PAKDD
2009
ACM
94views Data Mining» more  PAKDD 2009»
14 years 1 months ago
Item Preference Parameters from Grouped Ranking Observations
Given a set of rating data for a set of items, determining the values of items is a matter of importance and various probability models have been proposed. The Plackett-Luce model ...
Hideitsu Hino, Yu Fujimoto, Noboru Murata
ICWSM
2008
13 years 10 months ago
Recommendation of Multimedia Items by Link Analysis and Collaborative Filtering
We investigate two recommendation approaches suitable for online multimedia sharing services. Our first approach, UserRank, recommends items by global interestingness irrespective...
Davin Wong, Ella Bingham, Saara Hyvönen
RECSYS
2010
ACM
13 years 8 months ago
Group recommendations with rank aggregation and collaborative filtering
The majority of recommender systems are designed to make recommendations for individual users. However, in some circumstances the items to be selected are not intended for persona...
Linas Baltrunas, Tadas Makcinskas, Francesco Ricci
ICML
2006
IEEE
14 years 9 months ago
Learning user preferences for sets of objects
Most work on preference learning has focused on pairwise preferences or rankings over individual items. In this paper, we present a method for learning preferences over sets of it...
Marie desJardins, Eric Eaton, Kiri Wagstaff
JMLR
2010
135views more  JMLR 2010»
13 years 3 months ago
An Exponential Model for Infinite Rankings
This paper presents a statistical model for expressing preferences through rankings, when the number of alternatives (items to rank) is large. A human ranker will then typically r...
Marina Meila, Le Bao