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» On bootstrapping recommender systems
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SIGIR
2009
ACM
16 years 1 months ago
Temporal collaborative filtering with adaptive neighbourhoods
Recommender Systems, based on collaborative filtering (CF), aim to accurately predict user tastes, by minimising the mean error achieved on hidden test sets of user ratings, afte...
Neal Lathia, Stephen Hailes, Licia Capra
CONTEXT
2005
Springer
16 years 3 days ago
Design of context-aware systems for vehicles using complex system paradigms
Abstract. This paper argues that the driving task exhibits the properties of complex systems. Driving behavior emerges from the intricate and complex interactions between the drive...
Andry Rakotonirainy
IEEEARES
2007
IEEE
16 years 26 days ago
Reputation Management Survey
Electronic markets, distributed peer-to-peer applications and other forms of online collaboration are all based on mutual trust, which enables transacting peers to overcome the un...
Sini Ruohomaa, Lea Kutvonen, Eleni Koutrouli
AAAI
2006
15 years 8 months ago
A Value Theory of Meta-Learning Algorithms
We use game theory to analyze meta-learning algorithms. The objective of meta-learning is to determine which algorithm to apply on a given task. This is an instance of a more gene...
Abraham Bagherjeiran
CVPR
2007
IEEE
16 years 8 months ago
Kernel-Based 3D Tracking
We present a computer vision system for robust object tracking in 3D by combining evidence from multiple calibrated cameras. This kernel-based 3D tracker is automatically bootstra...
Ambrish Tyagi, Mark A. Keck, James W. Davis, Geras...