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» Convergent algorithms for collaborative filtering
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IIR
2010
13 years 8 months ago
Context-Dependent Recommendations with Items Splitting
Recommender systems are intelligent applications that help on-line users to tackle information overload by providing recommendations of relevant items. Collaborative Filtering (CF...
Linas Baltrunas, Francesco Ricci
RAS
2006
138views more  RAS 2006»
13 years 7 months ago
From pixels to multi-robot decision-making: A study in uncertainty
Mobile robots must cope with uncertainty from many sources along the path from interpreting raw sensor inputs to behavior selection to execution of the resulting primitive actions...
Peter Stone, Mohan Sridharan, Daniel Stronger, Gre...
ICWSM
2009
13 years 5 months ago
A Comparative Analysis of Trust-Enhanced Recommenders for Controversial Items
A particularly challenging task for recommender systems (RSs) is deciding whether to recommend an item that received a variety of high and low scores from its users. RSs that inco...
Patricia Victor, Chris Cornelis, Martine De Cock, ...
CIKM
2010
Springer
13 years 2 months ago
On bootstrapping recommender systems
Recommender systems perform much better on users for which they have more information. This gives rise to a problem of satisfying users new to a system. The problem is even more a...
Nadav Golbandi, Yehuda Koren, Ronny Lempel
ISBI
2002
IEEE
14 years 8 months ago
Joint estimation of cardiac kinematics and material parameters from noisy imaging data and uncertain mechanical model
There have been many efforts using image analysis algorithms to study cardiac kinematics, or using biomechanics strategies to study myocardial material properties. In this paper, ...
Huafeng Liu, Edward W. B. Lo, Pengcheng Shi