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» Mining data streams with periodically changing distributions
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KDD
2012
ACM
201views Data Mining» more  KDD 2012»
11 years 10 months ago
Learning from crowds in the presence of schools of thought
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
Yuandong Tian, Jun Zhu
SIGCOMM
2010
ACM
13 years 7 months ago
Energy proportionality of an enterprise network
Energy efficiency is becoming increasingly important in the operation of networking infrastructure, especially in enterprise and data center networks. While strategies for lowerin...
Priya Mahadevan, Sujata Banerjee, Puneet Sharma
SIGMOD
2008
ACM
138views Database» more  SIGMOD 2008»
14 years 7 months ago
Sampling time-based sliding windows in bounded space
Random sampling is an appealing approach to build synopses of large data streams because random samples can be used for a broad spectrum of analytical tasks. Users are often inter...
Rainer Gemulla, Wolfgang Lehner
WWW
2009
ACM
14 years 8 months ago
Collaborative filtering for orkut communities: discovery of user latent behavior
Users of social networking services can connect with each other by forming communities for online interaction. Yet as the number of communities hosted by such websites grows over ...
WenYen Chen, Jon-Chyuan Chu, Junyi Luan, Hongjie B...
WSDM
2012
ACM
207views Data Mining» more  WSDM 2012»
12 years 3 months ago
Domain bias in web search
This paper uncovers a new phenomenon in web search that we call domain bias — a user’s propensity to believe that a page is more relevant just because it comes from a particul...
Samuel Ieong, Nina Mishra, Eldar Sadikov, Li Zhang