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» Static community detection algorithms for evolving networks
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DIS
2009
Springer
14 years 2 months ago
CHRONICLE: A Two-Stage Density-Based Clustering Algorithm for Dynamic Networks
Abstract. Information networks, such as social networks and that extracted from bibliographic data, are changing dynamically over time. It is crucial to discover time-evolving comm...
Min-Soo Kim 0002, Jiawei Han
ISI
2004
Springer
14 years 26 days ago
Discovering Hidden Groups in Communication Networks
We describe models and efficient algorithms for detecting groups (communities) functioning in communication networks which attempt to hide their functionality – hidden groups. O...
Jeffrey Baumes, Mark K. Goldberg, Malik Magdon-Ism...
IJRR
2010
173views more  IJRR 2010»
13 years 6 months ago
Planning and Implementing Trajectories for Autonomous Underwater Vehicles to Track Evolving Ocean Processes Based on Predictions
Path planning and trajectory design for autonomous underwater vehicles (AUVs) is of great importance to the oceanographic research community because automated data collection is b...
Ryan N. Smith, Yi Chao, Peggy Li, David A. Caron, ...
WWW
2009
ACM
14 years 8 months ago
Extracting community structure through relational hypergraphs
Social media websites promote diverse user interaction on media objects as well as user actions with respect to other users. The goal of this work is to discover community structu...
Yu-Ru Lin, Jimeng Sun, Paul Castro, Ravi B. Konuru...
WEA
2010
Springer
316views Algorithms» more  WEA 2010»
14 years 19 days ago
Modularity-Driven Clustering of Dynamic Graphs
Maximizing the quality index modularity has become one of the primary methods for identifying the clustering structure within a graph. As contemporary networks are not static but e...
Robert Görke, Pascal Maillard, Christian Stau...