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KDD
2008
ACM
156views Data Mining» more  KDD 2008»
16 years 7 months ago
Can complex network metrics predict the behavior of NBA teams?
The United States National Basketball Association (NBA) is one of the most popular sports league in the world and is well known for moving a millionary betting market that uses th...
Antonio Alfredo Ferreira Loureiro, Pedro O. S. Vaz...
KDD
2008
ACM
165views Data Mining» more  KDD 2008»
16 years 7 months ago
Colibri: fast mining of large static and dynamic graphs
Low-rank approximations of the adjacency matrix of a graph are essential in finding patterns (such as communities) and detecting anomalies. Additionally, it is desirable to track ...
Hanghang Tong, Spiros Papadimitriou, Jimeng Sun, P...
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
16 years 7 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
KDD
2008
ACM
138views Data Mining» more  KDD 2008»
16 years 7 months ago
Quantitative evaluation of approximate frequent pattern mining algorithms
Traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life d...
Rohit Gupta, Gang Fang, Blayne Field, Michael Stei...
KDD
2008
ACM
147views Data Mining» more  KDD 2008»
16 years 7 months ago
Mobile call graphs: beyond power-law and lognormal distributions
We analyze a massive social network, gathered from the records of a large mobile phone operator, with more than a million users and tens of millions of calls. We examine the distr...
Mukund Seshadri, Sridhar Machiraju, Ashwin Sridhar...
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