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» Mining interesting sets and rules in relational databases
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CIKM
2005
Springer
14 years 2 months ago
Opportunity map: a visualization framework for fast identification of actionable knowledge
Data mining techniques frequently find a large number of patterns or rules, which make it very difficult for a human analyst to interpret the results and to find the truly interes...
Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Weimin Xia...
DATAMINE
2006
131views more  DATAMINE 2006»
13 years 9 months ago
A systematic approach to the assessment of fuzzy association rules
In order to allow for the analysis of data sets including numerical attributes, several generalizations of association rule mining based on fuzzy sets have been proposed in the li...
Didier Dubois, Eyke Hüllermeier, Henri Prade
PKDD
2005
Springer
110views Data Mining» more  PKDD 2005»
14 years 2 months ago
k-Anonymous Patterns
It is generally believed that data mining results do not violate the anonymity of the individuals recorded in the source database. In fact, data mining models and patterns, in orde...
Maurizio Atzori, Francesco Bonchi, Fosca Giannotti...
KDD
2007
ACM
249views Data Mining» more  KDD 2007»
14 years 9 months ago
The minimum consistent subset cover problem and its applications in data mining
In this paper, we introduce and study the Minimum Consistent Subset Cover (MCSC) problem. Given a finite ground set X and a constraint t, find the minimum number of consistent sub...
Byron J. Gao, Martin Ester, Jin-yi Cai, Oliver Sch...
GFKL
2006
Springer
78views Data Mining» more  GFKL 2006»
14 years 21 days ago
Putting Successor Variety Stemming to Work
Stemming algorithms find canonical forms for inflected words, e. g. for declined nouns or conjugated verbs. Since such a unification of words with respect to gender, number, time, ...
Benno Stein, Martin Potthast