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146
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CINQ
2004
Springer
157views Database» more  CINQ 2004»
15 years 5 months ago
Inductive Databases and Multiple Uses of Frequent Itemsets: The cInQ Approach
Inductive databases (IDBs) have been proposed to afford the problem of knowledge discovery from huge databases. With an IDB the user/analyst performs a set of very different operat...
Jean-François Boulicaut
121
Voted
DAGM
2006
Springer
15 years 5 months ago
Towards Unsupervised Discovery of Visual Categories
Recently, many approaches have been proposed for visual object category detection. They vary greatly in terms of how much supervision is needed. High performance object detection m...
Mario Fritz, Bernt Schiele
105
Voted
GFKL
2006
Springer
78views Data Mining» more  GFKL 2006»
15 years 5 months 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
KDD
2010
ACM
265views Data Mining» more  KDD 2010»
15 years 3 months ago
Scalable influence maximization for prevalent viral marketing in large-scale social networks
Influence maximization, defined by Kempe, Kleinberg, and Tardos (2003), is the problem of finding a small set of seed nodes in a social network that maximizes the spread of influe...
Wei Chen, Chi Wang, Yajun Wang
CORR
2010
Springer
74views Education» more  CORR 2010»
15 years 1 months ago
Significance of Classification Techniques in Prediction of Learning Disabilities
The aim of this study is to show the importance of two classification techniques, viz. decision tree and clustering, in prediction of learning disabilities (LD) of school-age chil...
Julie M. David, Kannan Balakrishnan