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» Mining Very Large Databases
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KDD
1997
ACM
169views Data Mining» more  KDD 1997»
14 years 2 months ago
Learning to Extract Text-Based Information from the World Wide Web
Thereis a wealthof informationto be minedfromnarrative text on the WorldWideWeb.Unfortunately, standard natural language processing (NLP)extraction techniques expect full, grammat...
Stephen Soderland
SDM
2004
SIAM
165views Data Mining» more  SDM 2004»
13 years 11 months ago
Visualizing RFM Segmentation
Segmentation based on RFM (Recency, Frequency, and Monetary) has been used for over 50 years by direct marketers to target a subset of their customers, save mailing costs, and imp...
Ron Kohavi, Rajesh Parekh
AIIA
2005
Springer
14 years 3 months ago
Towards Fault-Tolerant Formal Concept Analysis
Given Boolean data sets which record properties of objects, Formal Concept Analysis is a well-known approach for knowledge discovery. Recent application domains, e.g., for very lar...
Ruggero G. Pensa, Jean-François Boulicaut
ICPP
2000
IEEE
14 years 2 months ago
A Scalable Parallel Subspace Clustering Algorithm for Massive Data Sets
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
Harsha S. Nagesh, Sanjay Goil, Alok N. Choudhary
EDBT
2010
ACM
185views Database» more  EDBT 2010»
14 years 4 months ago
Optimizing joins in a map-reduce environment
Implementations of map-reduce are being used to perform many operations on very large data. We examine strategies for joining several relations in the map-reduce environment. Our ...
Foto N. Afrati, Jeffrey D. Ullman