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» Mining Antagonistic Communities from Social Networks
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KDD
2009
ACM
180views Data Mining» more  KDD 2009»
14 years 8 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
BMCBI
2005
152views more  BMCBI 2005»
13 years 7 months ago
GeneKeyDB: A lightweight, gene-centric, relational database to support data mining environments
Background: The analysis of biological data is greatly enhanced by existing or emerging databases. Most existing databases, with few exceptions are not designed to easily support ...
S. A. Kirov, X. Peng, E. Baker, D. Schmoyer, B. Zh...
PKDD
2009
Springer
134views Data Mining» more  PKDD 2009»
14 years 2 months ago
Mining Graph Evolution Rules
In this paper we introduce graph-evolution rules, a novel type of frequency-based pattern that describe the evolution of large networks over time, at a local level. Given a sequenc...
Michele Berlingerio, Francesco Bonchi, Björn ...
SDM
2007
SIAM
143views Data Mining» more  SDM 2007»
13 years 9 months ago
Patterns of Cascading Behavior in Large Blog Graphs
How do blogs cite and influence each other? How do such links evolve? Does the popularity of old blog posts drop exponentially with time? These are some of the questions that we ...
Jure Leskovec, Mary McGlohon, Christos Faloutsos, ...
SIGIR
2011
ACM
12 years 10 months ago
Social context summarization
We study a novel problem of social context summarization for Web documents. Traditional summarization research has focused on extracting informative sentences from standard docume...
Zi Yang, Keke Cai, Jie Tang, Li Zhang, Zhong Su, J...