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KDD
2007
ACM
179views Data Mining» more  KDD 2007»
14 years 3 months ago
Mining statistically important equivalence classes and delta-discriminative emerging patterns
The support-confidence framework is the most common measure used in itemset mining algorithms, for its antimonotonicity that effectively simplifies the search lattice. This com...
Jinyan Li, Guimei Liu, Limsoon Wong
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
14 years 9 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, ...
IMC
2005
ACM
14 years 2 months ago
Combining Filtering and Statistical Methods for Anomaly Detection
In this work we develop an approach for anomaly detection for large scale networks such as that of an enterprize or an ISP. The traffic patterns we focus on for analysis are that...
Augustin Soule, Kavé Salamatian, Nina Taft
NC
1998
102views Neural Networks» more  NC 1998»
13 years 10 months ago
Outliers and Bayesian Inference
In this paper we report about an investigation in which we studied the properties of Bayes' inferred neural network classifiers in the context of outlier detection. The proble...
Peter Sykacek
SAC
2008
ACM
13 years 8 months ago
Crime scene classification
In this paper we provide a study about crime scenes and its features used in criminal investigations. We argue that the crime scene provides a large set of features that can be us...
Ricardo O. Abu Hana, Cinthia Obladen de Almendra F...