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» A Comparative Evaluation of Term Recognition Algorithms
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CIKM
2006
Springer
15 years 8 months ago
Incremental hierarchical clustering of text documents
Incremental hierarchical text document clustering algorithms are important in organizing documents generated from streaming on-line sources, such as, Newswire and Blogs. However, ...
Nachiketa Sahoo, Jamie Callan, Ramayya Krishnan, G...
127
Voted
CEC
2005
IEEE
15 years 10 months ago
Adaptive cluster covering and evolutionary approach: comparison, differences and similarities
In case the objective function to be minimized is not known analytically and no assumption can be made about the single extremum, global optimization (GO) methods must be used. Pap...
Dimitri P. Solomatine
152
Voted
DASFAA
2009
IEEE
133views Database» more  DASFAA 2009»
15 years 11 months ago
Probabilistic Ranking in Uncertain Vector Spaces
Abstract. In many application domains, e.g. sensor databases, traffic management or recognition systems, objects have to be compared based on positionally and existentially uncert...
Thomas Bernecker, Hans-Peter Kriegel, Matthias Ren...
KDD
2012
ACM
281views Data Mining» more  KDD 2012»
13 years 7 months ago
Active spectral clustering via iterative uncertainty reduction
Spectral clustering is a widely used method for organizing data that only relies on pairwise similarity measurements. This makes its application to non-vectorial data straightforw...
Fabian L. Wauthier, Nebojsa Jojic, Michael I. Jord...
239
Voted
SGAI
2010
Springer
15 years 2 months ago
Induction of Modular Classification Rules: Using Jmax-pruning
The Prism family of algorithms induces modular classification rules which, in contrast to decision tree induction algorithms, do not necessarily fit together into a decision tree s...
Frederic T. Stahl, Max Bramer