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» Phenomenal Data Mining: From Data to Phenomena
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110
Voted
SODA
2001
ACM
147views Algorithms» more  SODA 2001»
15 years 3 months ago
Sublinear time approximate clustering
Clustering is of central importance in a number of disciplines including Machine Learning, Statistics, and Data Mining. This paper has two foci: 1 It describes how existing algori...
Nina Mishra, Daniel Oblinger, Leonard Pitt
CIDM
2009
IEEE
15 years 8 months ago
Evolving decision trees using oracle guides
—Some data mining problems require predictive models to be not only accurate but also comprehensible. Comprehensibility enables human inspection and understanding of the model, m...
Ulf Johansson, Lars Niklasson
125
Voted
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
16 years 2 months ago
Query result clustering for object-level search
Query result clustering has recently attracted a lot of attention to provide users with a succinct overview of relevant results. However, little work has been done on organizing t...
Jongwuk Lee, Seung-won Hwang, Zaiqing Nie, Ji-Rong...
KDD
2005
ACM
158views Data Mining» more  KDD 2005»
16 years 2 months ago
Adversarial learning
Many classification tasks, such as spam filtering, intrusion detection, and terrorism detection, are complicated by an adversary who wishes to avoid detection. Previous work on ad...
Daniel Lowd, Christopher Meek
KDD
2002
ACM
130views Data Mining» more  KDD 2002»
16 years 2 months ago
Learning domain-independent string transformation weights for high accuracy object identification
The task of object identification occurs when integrating information from multiple websites. The same data objects can exist in inconsistent text formats across sites, making it ...
Sheila Tejada, Craig A. Knoblock, Steven Minton