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» Handling Data Skew in MapReduce
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KDD
2009
ACM
146views Data Mining» more  KDD 2009»
14 years 4 months ago
Mining in a mobile environment
Distributed PRocessing in Mobile Environments (DPRiME) is a framework for processing large data sets across an ad-hoc network. Developed to address the shortcomings of Google’s ...
Sean McRoskey, James Notwell, Nitesh V. Chawla, Ch...
PKDD
2010
Springer
129views Data Mining» more  PKDD 2010»
13 years 8 months ago
Learning Algorithms for Link Prediction Based on Chance Constraints
In this paper, we consider the link prediction problem, where we are given a partial snapshot of a network at some time and the goal is to predict the additional links formed at a ...
Janardhan Rao Doppa, Jun Yu, Prasad Tadepalli, Lis...
PODS
2006
ACM
122views Database» more  PODS 2006»
14 years 10 months ago
Space- and time-efficient deterministic algorithms for biased quantiles over data streams
Skew is prevalent in data streams, and should be taken into account by algorithms that analyze the data. The problem of finding "biased quantiles"-- that is, approximate...
Graham Cormode, Flip Korn, S. Muthukrishnan, Dives...
PVLDB
2008
77views more  PVLDB 2008»
13 years 9 months ago
Community-driven data grids
Beyond already existing huge data volumes, e-science communities face major challenges in managing the anticipated data deluge of forthcoming projects. Community-driven data grids...
Tobias Scholl, Alfons Kemper
KDD
2009
ACM
210views Data Mining» more  KDD 2009»
14 years 10 months ago
Large-scale behavioral targeting
Behavioral targeting (BT) leverages historical user behavior to select the ads most relevant to users to display. The state-of-the-art of BT derives a linear Poisson regression mo...
Ye Chen, Dmitry Pavlov, John F. Canny