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» Using Concept Lattices to Support Service Selection
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ICIP
2008
IEEE
16 years 26 days ago
Cross-domain learning methods for high-level visual concept classification
Exploding amounts of multimedia data increasingly require automatic indexing and classification, e.g. training classifiers to produce high-level features, or semantic concepts, ch...
Wei Jiang, Eric Zavesky, Shih-Fu Chang, Alexander ...
MIDDLEWARE
2007
Springer
15 years 5 months ago
Flexible matching and ranking of web service advertisements
With the growing number of service advertisements in service marketplaces, there is a need for matchmakers which select and rank functionally similar services based on nonfunction...
Navid Ahmadi, Walter Binder
BIRTHDAY
2009
Springer
15 years 6 months ago
Data Modeling in Dataspace Support Platforms
Data integration has been an important area of research for several years. However, such systems suffer from one of the main drawbacks of database systems: the need to invest signi...
Anish Das Sarma, Xin Luna Dong, Alon Y. Halevy
ICML
2004
IEEE
15 years 12 months ago
Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5
Text categorization algorithms usually represent documents as bags of words and consequently have to deal with huge numbers of features. Most previous studies found that the major...
Evgeniy Gabrilovich, Shaul Markovitch
EMO
2005
Springer
194views Optimization» more  EMO 2005»
15 years 4 months ago
An EMO Algorithm Using the Hypervolume Measure as Selection Criterion
Abstract. The hypervolume measure is one of the most frequently applied measures for comparing the results of evolutionary multiobjective optimization algorithms (EMOA). The idea t...
Michael Emmerich, Nicola Beume, Boris Naujoks