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138
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WWW
2004
ACM
16 years 4 months ago
Shilling recommender systems for fun and profit
Recommender systems have emerged in the past several years as an effective way to help people cope with the problem of information overload. One application in which they have bec...
Shyong K. Lam, John Riedl
KDD
2009
ACM
364views Data Mining» more  KDD 2009»
16 years 4 months ago
Causality quantification and its applications: structuring and modeling of multivariate time series
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
Takashi Shibuya, Tatsuya Harada, Yasuo Kuniyoshi
131
Voted
KDD
2007
ACM
191views Data Mining» more  KDD 2007»
16 years 4 months ago
Modeling relationships at multiple scales to improve accuracy of large recommender systems
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...
Robert M. Bell, Yehuda Koren, Chris Volinsky
137
Voted
ICFP
2008
ACM
16 years 3 months ago
Compiling self-adjusting programs with continuations
Self-adjusting programs respond automatically and efficiently to input changes by tracking the dynamic data dependences of the computation and incrementally updating the output as...
Ruy Ley-Wild, Matthew Fluet, Umut A. Acar
117
Voted
ICFP
2006
ACM
16 years 3 months ago
Static typing for a faulty lambda calculus
A transient hardware fault occurs when an energetic particle strikes a transistor, causing it to change state. These faults do not cause permanent damage, but may result in incorr...
David Walker, Lester W. Mackey, Jay Ligatti, Georg...