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» Approximate data mining in very large relational data
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KDD
2005
ACM
171views Data Mining» more  KDD 2005»
16 years 2 months ago
Deriving marketing intelligence from online discussion
Weblogs and message boards provide online forums for discussion that record the voice of the public. Woven into this mass of discussion is a wide range of opinion and commentary a...
Natalie S. Glance, Matthew Hurst, Kamal Nigam, Mat...
KDD
2003
ACM
156views Data Mining» more  KDD 2003»
16 years 2 months ago
Fast vertical mining using diffsets
A number of vertical mining algorithms have been proposed recently for association mining, which have shown to be very effective and usually outperform horizontal approaches. The ...
Mohammed Javeed Zaki, Karam Gouda
129
Voted
PKDD
2010
Springer
169views Data Mining» more  PKDD 2010»
14 years 11 months ago
Classification with Sums of Separable Functions
Abstract. We present a novel approach for classification using a discretised function representation which is independent of the data locations. We construct the classifier as a su...
Jochen Garcke
DCC
2011
IEEE
14 years 8 months ago
Deplump for Streaming Data
We present a general-purpose, lossless compressor for streaming data. This compressor is based on the deplump probabilistic compressor for batch data. Approximations to the infere...
Nicholas Bartlett, Frank Wood
123
Voted
VLDB
1998
ACM
192views Database» more  VLDB 1998»
15 years 5 months ago
Algorithms for Mining Distance-Based Outliers in Large Datasets
This paper deals with finding outliers (exceptions) in large, multidimensional datasets. The identification of outliers can lead to the discovery of truly unexpected knowledge in ...
Edwin M. Knorr, Raymond T. Ng