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KDD
2007
ACM
209views Data Mining» more  KDD 2007»
16 years 7 months ago
Temporal causal modeling with graphical granger methods
The need for mining causality, beyond mere statistical correlations, for real world problems has been recognized widely. Many of these applications naturally involve temporal data...
Andrew Arnold, Yan Liu, Naoki Abe
KDD
2006
ACM
145views Data Mining» more  KDD 2006»
16 years 7 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...
SIGIR
2012
ACM
13 years 10 months ago
Improving searcher models using mouse cursor activity
Web search components such as ranking and query suggestions analyze the user data provided in query and click logs. While this data is easy to collect and provides information abo...
Jeff Huang, Ryen W. White, Georg Buscher, Kuansan ...
KDD
2005
ACM
161views Data Mining» more  KDD 2005»
16 years 7 months ago
Combining email models for false positive reduction
Machine learning and data mining can be effectively used to model, classify and discover interesting information for a wide variety of data including email. The Email Mining Toolk...
Shlomo Hershkop, Salvatore J. Stolfo
218
Voted
KDD
2004
ACM
179views Data Mining» more  KDD 2004»
16 years 7 months ago
1-dimensional splines as building blocks for improving accuracy of risk outcomes models
Transformation of both the response variable and the predictors is commonly used in fitting regression models. However, these transformation methods do not always provide the maxi...
David S. Vogel, Morgan C. Wang