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» Using Data Mining in MURA Graphic Problems
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SDM
2008
SIAM
97views Data Mining» more  SDM 2008»
15 years 5 months ago
Efficient Distribution Mining and Classification
We define and solve the problem of "distribution classification", and, in general, "distribution mining". Given n distributions (i.e., clouds) of multi-dimensi...
Yasushi Sakurai, Rosalynn Chong, Lei Li, Christos ...
IQ
2007
15 years 5 months ago
Emergent Data Quality Annotation And Visualization
: The systematic assessment, storage, and retrieval of data quality scores has proven to be an elusive problem, often tackled only with classifications, questionnaires, and models....
Paul Führing, Felix Naumann
EDBT
2000
ACM
15 years 7 months ago
Mining Classification Rules from Datasets with Large Number of Many-Valued Attributes
Decision tree induction algorithms scale well to large datasets for their univariate and divide-and-conquer approach. However, they may fail in discovering effective knowledge when...
Giovanni Giuffrida, Wesley W. Chu, Dominique M. Ha...
KDD
2007
ACM
167views Data Mining» more  KDD 2007»
16 years 4 months ago
Generalized component analysis for text with heterogeneous attributes
We present a class of richly structured, undirected hidden variable models suitable for simultaneously modeling text along with other attributes encoded in different modalities. O...
Xuerui Wang, Chris Pal, Andrew McCallum
MLDM
2007
Springer
15 years 10 months ago
Applying Frequent Sequence Mining to Identify Design Flaws in Enterprise Software Systems
In this paper we show how frequent sequence mining (FSM) can be applied to data produced by monitoring distributed enterprise applications. In particular we show how we applied FSM...
Trevor Parsons, John Murphy, Patrick O'Sullivan