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» A Perspective on Databases and Data Mining
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CORR
2000
Springer
120views Education» more  CORR 2000»
15 years 4 months ago
Scaling Up Inductive Logic Programming by Learning from Interpretations
When comparing inductive logic programming (ILP) and attribute-value learning techniques, there is a trade-off between expressive power and efficiency. Inductive logic programming ...
Hendrik Blockeel, Luc De Raedt, Nico Jacobs, Bart ...
PODS
2009
ACM
134views Database» more  PODS 2009»
16 years 4 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...
VLDB
2004
ACM
163views Database» more  VLDB 2004»
15 years 9 months ago
Compressing Large Boolean Matrices using Reordering Techniques
Large boolean matrices are a basic representational unit in a variety of applications, with some notable examples being interactive visualization systems, mining large graph struc...
David S. Johnson, Shankar Krishnan, Jatin Chhugani...
GIS
2009
ACM
15 years 9 months ago
REG^2: a regional regression framework for geo-referenced datasets
Traditional regression analysis derives global relationships between variables and neglects spatial variations in variables. Hence they lack the ability to systematically discover...
Oner Ulvi Celepcikay, Christoph F. Eick
CIKM
2008
Springer
15 years 6 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan