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KAIS
2007
75views more  KAIS 2007»
13 years 7 months ago
Non-redundant data clustering
Data clustering is a popular approach for automatically finding classes, concepts, or groups of patterns. In practice this discovery process should avoid redundancies with existi...
David Gondek, Thomas Hofmann
KDD
2000
ACM
115views Data Mining» more  KDD 2000»
13 years 11 months ago
A framework for specifying explicit bias for revision of approximate information extraction rules
Information extraction is one of the most important techniques used in Text Mining. One of the main problems in building information extraction (IE) systems is that the knowledge ...
Ronen Feldman, Yair Liberzon, Binyamin Rosenfeld, ...
ICDM
2006
IEEE
130views Data Mining» more  ICDM 2006»
14 years 1 months ago
A Framework for Regional Association Rule Mining in Spatial Datasets
The immense explosion of geographically referenced data calls for efficient discovery of spatial knowledge. One critical requirement for spatial data mining is the capability to ...
Wei Ding 0003, Christoph F. Eick, Jing Wang 0007, ...
KDD
2009
ACM
243views Data Mining» more  KDD 2009»
14 years 8 months ago
Exploiting Wikipedia as external knowledge for document clustering
In traditional text clustering methods, documents are represented as "bags of words" without considering the semantic information of each document. For instance, if two ...
Xiaohua Hu, Xiaodan Zhang, Caimei Lu, E. K. Park, ...
BIODATAMINING
2008
178views more  BIODATAMINING 2008»
13 years 8 months ago
Clustering-based approaches to SAGE data mining
Serial analysis of gene expression (SAGE) is one of the most powerful tools for global gene expression profiling. It has led to several biological discoveries and biomedical appli...
Haiying Wang, Huiru Zheng, Francisco Azuaje