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» Inferring Knowledge from a Large Semantic Network
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GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
15 years 5 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
ICCS
2007
Springer
15 years 10 months ago
Quo Vadis, CS? - On the (non)-Impact of Conceptual Structures on the Semantic Web
Abstract. Conceptual Structures is a field of research which shares abstract concepts and interests with recent work on knowledge representation for the Semantic Web. However, whi...
Sebastian Rudolph, Markus Krötzsch, Pascal Hi...
ECAI
2010
Springer
15 years 5 months ago
On Semantic Update Operators for Answer-Set Programs
Logic programs under the stable models semantics, or answer-set programs, provide an expressive rule based knowledge representation framework, featuring formal, declarative and wel...
Martin Slota, João Leite
BMCBI
2008
174views more  BMCBI 2008»
15 years 4 months ago
Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset
Background: Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interact...
Cédric Auliac, Vincent Frouin, Xavier Gidro...
ER
2004
Springer
161views Database» more  ER 2004»
15 years 9 months ago
Towards a Statistically Semantic Web
The envisioned Semantic Web aims to provide richly annotated and explicitly structured Web pages in XML, RDF, or description logics, based upon underlying ontologies and thesauri. ...
Gerhard Weikum, Jens Graupmann, Ralf Schenkel, Mar...