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SDM
2009
SIAM
192views Data Mining» more  SDM 2009»
15 years 11 months ago
Mining Cohesive Patterns from Graphs with Feature Vectors.
The increasing availability of network data is creating a great potential for knowledge discovery from graph data. In many applications, feature vectors are given in addition to g...
Arash Rafiey, Flavia Moser, Martin Ester, Recep Co...
FLAIRS
2010
15 years 4 months ago
Handling of Numeric Ranges for Graph-Based Knowledge Discovery
Nowadays, graph-based knowledge discovery algorithms do not consider numeric attributes (they are discarded in the preprocessing step, or they are treated as alphanumeric values w...
Oscar E. Romero, Jesus A. Gonzalez, Lawrence B. Ho...
124
Voted
COMAD
2009
15 years 3 months ago
Large Maximal Cliques Enumeration in Large Sparse Graphs
Identifying communities in social networks is a problem of great interest. One popular type of community is where every member of the community knows all others, which can be view...
Natwar Modani, Kuntal Dey
142
Voted
CGF
2010
121views more  CGF 2010»
15 years 2 months ago
GraphDice: A System for Exploring Multivariate Social Networks
Social networks collected by historians or sociologists typically have a large number of actors and edge attributes. Applying social network analysis (SNA) algorithms to these net...
Anastasia Bezerianos, Fanny Chevalier, Pierre Drag...
CORR
2011
Springer
169views Education» more  CORR 2011»
14 years 5 months ago
Pseudo-random graphs and bit probe schemes with one-sided error
We study probabilistic bit-probe schemes for the membership problem. Given a set A of at most n elements from the universe of size m we organize such a structure that queries of t...
Andrei E. Romashchenko