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KDD
2008
ACM
174views Data Mining» more  KDD 2008»
16 years 6 months ago
Automatic identification of quasi-experimental designs for discovering causal knowledge
Researchers in the social and behavioral sciences routinely rely on quasi-experimental designs to discover knowledge from large databases. Quasi-experimental designs (QEDs) exploi...
David D. Jensen, Andrew S. Fast, Brian J. Taylor, ...
KDD
2006
ACM
113views Data Mining» more  KDD 2006»
16 years 6 months ago
A new efficient probabilistic model for mining labeled ordered trees
Mining frequent patterns is a general and important issue in data mining. Complex and unstructured (or semi-structured) datasets have appeared in major data mining applications, i...
Kosuke Hashimoto, Kiyoko F. Aoki-Kinoshita, Nobuhi...
KDD
2003
ACM
449views Data Mining» more  KDD 2003»
16 years 6 months ago
Passenger-based predictive modeling of airline no-show rates
Airlines routinely overbook flights based on the expectation that some fraction of booked passengers will not show for each flight. Accurate forecasts of the expected number of no...
Richard D. Lawrence, Se June Hong, Jacques Cherrie...
KDD
2002
ACM
175views Data Mining» more  KDD 2002»
16 years 6 months ago
Mining product reputations on the Web
Knowing the reputations of your own and/or competitors' products is important for marketing and customer relationship management. It is, however, very costly to collect and a...
Satoshi Morinaga, Kenji Yamanishi, Kenji Tateishi,...
KDD
2001
ACM
163views Data Mining» more  KDD 2001»
16 years 6 months ago
The "DGX" distribution for mining massive, skewed data
Skewed distributions appear very often in practice. Unfortunately, the traditional Zipf distribution often fails to model them well. In this paper, we propose a new probability di...
Zhiqiang Bi, Christos Faloutsos, Flip Korn
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