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» Learning Preferences for Multiclass Problems
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SIGIR
2011
ACM
12 years 10 months ago
Functional matrix factorizations for cold-start recommendation
A key challenge in recommender system research is how to effectively profile new users, a problem generally known as cold-start recommendation. Recently the idea of progressivel...
Ke Zhou, Shuang-Hong Yang, Hongyuan Zha
SIGECOM
2006
ACM
139views ECommerce» more  SIGECOM 2006»
14 years 1 months ago
Playing games in many possible worlds
In traditional game theory, players are typically endowed with exogenously given knowledge of the structure of the game—either full omniscient knowledge or partial but fixed in...
Matt Lepinski, David Liben-Nowell, Seth Gilbert, A...
KDD
2012
ACM
247views Data Mining» more  KDD 2012»
11 years 10 months ago
Integrating meta-path selection with user-guided object clustering in heterogeneous information networks
Real-world, multiple-typed objects are often interconnected, forming heterogeneous information networks. A major challenge for link-based clustering in such networks is its potent...
Yizhou Sun, Brandon Norick, Jiawei Han, Xifeng Yan...
SIGIR
2009
ACM
14 years 2 months ago
Fast nonparametric matrix factorization for large-scale collaborative filtering
With the sheer growth of online user data, it becomes challenging to develop preference learning algorithms that are sufficiently flexible in modeling but also affordable in com...
Kai Yu, Shenghuo Zhu, John D. Lafferty, Yihong Gon...
SIGIR
2009
ACM
14 years 2 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