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KDD
2010
ACM
265views Data Mining» more  KDD 2010»
13 years 11 months ago
Combining predictions for accurate recommender systems
We analyze the application of ensemble learning to recommender systems on the Netflix Prize dataset. For our analysis we use a set of diverse state-of-the-art collaborative filt...
Michael Jahrer, Andreas Töscher, Robert Legen...
RECSYS
2009
ACM
14 years 2 months ago
Harnessing the power of "favorites" lists for recommendation systems
We propose a novel collaborative recommendation approach to take advantage of the information available in user-created lists. Our approach assumes associations among any two item...
Maryam Khezrzadeh, Alex Thomo, William W. Wadge
ICDM
2003
IEEE
154views Data Mining» more  ICDM 2003»
14 years 28 days ago
MaPle: A Fast Algorithm for Maximal Pattern-based Clustering
Pattern-based clustering is important in many applications, such as DNA micro-array data analysis, automatic recommendation systems and target marketing systems. However, pattern-...
Jian Pei, Xiaoling Zhang, Moonjung Cho, Haixun Wan...
SIGMOD
2008
ACM
167views Database» more  SIGMOD 2008»
14 years 7 months ago
DiMaC: a system for cleaning disguised missing data
In some applications such as filling in a customer information form on the web, some missing values may not be explicitly represented as such, but instead appear as potentially va...
Ming Hua, Jian Pei
ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
14 years 2 months ago
A Bayesian approach to empirical local linearization for robotics
— Local linearizations are ubiquitous in the control of robotic systems. Analytical methods, if available, can be used to obtain the linearization, but in complex robotics system...
Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, St...