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» Assessing Data Mining Results on Matrices with Randomization
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SDM
2009
SIAM
167views Data Mining» more  SDM 2009»
14 years 4 months ago
Detecting Communities in Social Networks Using Max-Min Modularity.
Many datasets can be described in the form of graphs or networks where nodes in the graph represent entities and edges represent relationships between pairs of entities. A common ...
Jiyang Chen, Osmar R. Zaïane, Randy Goebel
KDD
2009
ACM
140views Data Mining» more  KDD 2009»
14 years 8 months ago
Improving clustering stability with combinatorial MRFs
: ? Improving Clustering Stability with Combinatorial MRFs Bekkerman, Ron; Scholz, Martin; Viswanathan, Krishnamurthy HP Laboratories HPL-2009-46 Clustering stability, combinatoria...
Ron Bekkerman, Martin Scholz, Krishnamurthy Viswan...
BMCBI
2004
173views more  BMCBI 2004»
13 years 7 months ago
d-matrix - database exploration, visualization and analysis
Background: Motivated by a biomedical database set up by our group, we aimed to develop a generic database front-end with embedded knowledge discovery and analysis features. A maj...
Dominik Seelow, Raffaello Galli, Siegrun Mebus, Ha...
INFOCOM
2010
IEEE
13 years 7 months ago
Walking in Facebook: A Case Study of Unbiased Sampling of OSNs
With more than 250 million active users, Facebook (FB) is currently one of the most important online social networks. Our goal in this paper is to obtain a representative (unbiased...
Minas Gjoka, Maciej Kurant, Carter T. Butts, Athin...
PODS
2009
ACM
134views Database» more  PODS 2009»
14 years 8 months ago
An efficient rigorous approach for identifying statistically significant frequent itemsets
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is b...
Adam Kirsch, Michael Mitzenmacher, Andrea Pietraca...