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KDD
2006
ACM
198views Data Mining» more  KDD 2006»
16 years 4 months ago
CFI-Stream: mining closed frequent itemsets in data streams
Mining frequent closed itemsets provides complete and condensed information for non-redundant association rules generation. Extensive studies have been done on mining frequent clo...
Nan Jiang, Le Gruenwald
KDD
2005
ACM
124views Data Mining» more  KDD 2005»
16 years 4 months ago
Scalable discovery of hidden emails from large folders
The popularity of email has triggered researchers to look for ways to help users better organize the enormous amount of information stored in their email folders. One challenge th...
Giuseppe Carenini, Raymond T. Ng, Xiaodong Zhou
KDD
2005
ACM
109views Data Mining» more  KDD 2005»
16 years 4 months ago
Formulating distance functions via the kernel trick
Tasks of data mining and information retrieval depend on a good distance function for measuring similarity between data instances. The most effective distance function must be for...
Gang Wu, Edward Y. Chang, Navneet Panda
KDD
2005
ACM
145views Data Mining» more  KDD 2005»
16 years 4 months ago
Using and Learning Semantics in Frequent Subgraph Mining
The search for frequent subgraphs is becoming increasingly important in many application areas including Web mining and bioinformatics. Any use of graph structures in mining, howev...
Bettina Berendt
KDD
2003
ACM
160views Data Mining» more  KDD 2003»
16 years 4 months ago
Playing hide-and-seek with correlations
We present a method for very high-dimensional correlation analysis. The method relies equally on rigorous search strategies and on human interaction. At each step, the method cons...
Chris Jermaine
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