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» Edge Anonymity in Social Network Graphs
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NIPS
2008
13 years 10 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
ICDE
2010
IEEE
240views Database» more  ICDE 2010»
14 years 1 months ago
Top-K aggregation queries over large networks
Searching and mining large graphs today is critical to a variety of application domains, ranging from personalized recommendation in social networks, to searches for functional ass...
Xifeng Yan, Bin He, Feida Zhu, Jiawei Han
CORR
2011
Springer
202views Education» more  CORR 2011»
13 years 3 months ago
Multi-skill Collaborative Teams based on Densest Subgraphs
We consider the problem of identifying a team of skilled individuals for collaboration, in the presence of a social network. Each node in the input social network may be an expert...
Amita Gajewar, Atish Das Sarma
CSUR
1999
159views more  CSUR 1999»
13 years 8 months ago
Hubs, authorities, and communities
The Web can be naturally modeled as a directed graph, consisting of a set of abstract nodes (the pages) joined by directional edges (the hyperlinks). Hyperlinks encode a considerab...
Jon M. Kleinberg
MM
2009
ACM
198views Multimedia» more  MM 2009»
14 years 1 months ago
Scalable detection of partial near-duplicate videos by visual-temporal consistency
Following the exponential growth of social media, there now exist huge repositories of videos online. Among the huge volumes of videos, there exist large numbers of near-duplicate...
Hung-Khoon Tan, Chong-Wah Ngo, Richang Hong, Tat-S...