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KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 5 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
16 years 5 months ago
Turning down the noise in the blogosphere
In recent years, the blogosphere has experienced a substantial increase in the number of posts published daily, forcing users to cope with information overload. The task of guidin...
Khalid El-Arini, Gaurav Veda, Dafna Shahaf, Carlos...
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KDD
2009
ACM
230views Data Mining» more  KDD 2009»
16 years 5 months ago
Analyzing patterns of user content generation in online social networks
Various online social networks (OSNs) have been developed rapidly on the Internet. Researchers have analyzed different properties of such OSNs, mainly focusing on the formation an...
Lei Guo, Enhua Tan, Songqing Chen, Xiaodong Zhang,...
KDD
2009
ACM
347views Data Mining» more  KDD 2009»
16 years 5 months ago
Network anomaly detection based on Eigen equation compression
This paper addresses the issue of unsupervised network anomaly detection. In recent years, networks have played more and more critical roles. Since their outages cause serious eco...
Shunsuke Hirose, Kenji Yamanishi, Takayuki Nakata,...
KDD
2009
ACM
173views Data Mining» more  KDD 2009»
16 years 5 months ago
Constant-factor approximation algorithms for identifying dynamic communities
We propose two approximation algorithms for identifying communities in dynamic social networks. Communities are intuitively characterized as "unusually densely knit" sub...
Chayant Tantipathananandh, Tanya Y. Berger-Wolf
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