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» Learning Classifiers from Semantically Heterogeneous Data
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CVPR
2008
IEEE
14 years 10 months ago
Object categorization using co-occurrence, location and appearance
In this work we introduce a novel approach to object categorization that incorporates two types of context ? cooccurrence and relative location ? with local appearancebased featur...
Carolina Galleguillos, Andrew Rabinovich, Serge Be...
SPLST
2003
13 years 10 months ago
Compacting XML Documents
Abstract. Nowadays one of the most common formats for storing information is XML. The size of XML documents can be rather large, and they may contain redundant attributes which can...
Miklós Kálmán, Ferenc Havasi,...
SIGMOD
2008
ACM
131views Database» more  SIGMOD 2008»
14 years 8 months ago
Discovering topical structures of databases
The increasing complexity of enterprise databases and the prevalent lack of documentation incur significant cost in both understanding and integrating the databases. Existing solu...
Wensheng Wu, Berthold Reinwald, Yannis Sismanis, R...
AND
2010
13 years 6 months ago
Reshaping automatic speech transcripts for robust high-level spoken document analysis
High-level spoken document analysis is required in many applications seeking access to the semantic content of audio data, such as information retrieval, machine translation or au...
Julien Fayolle, Fabienne Moreau, Christian Raymond...
COR
2006
97views more  COR 2006»
13 years 8 months ago
Evaluating the performance of cost-based discretization versus entropy- and error-based discretization
Discretization is defined as the process that divides continuous numeric values into intervals of discrete categorical values. In this article, the concept of cost-based discretiz...
Davy Janssens, Tom Brijs, Koen Vanhoof, Geert Wets