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CVPR
2008
IEEE
14 years 9 months ago
Unsupervised discovery of visual object class hierarchies
Objects in the world can be arranged into a hierarchy based on their semantic meaning (e.g. organism ? animal ? feline ? cat). What about defining a hierarchy based on the visual ...
Josef Sivic, Bryan C. Russell, Andrew Zisserman, W...
GECCO
2006
Springer
195views Optimization» more  GECCO 2006»
13 years 11 months ago
Studying XCS/BOA learning in Boolean functions: structure encoding and random Boolean functions
Recently, studies with the XCS classifier system on Boolean functions have shown that in certain types of functions simple crossover operators can lead to disruption and, conseque...
Martin V. Butz, Martin Pelikan
IJCAI
2007
13 years 9 months ago
Supervised Latent Semantic Indexing Using Adaptive Sprinkling
Latent Semantic Indexing (LSI) has been shown to be effective in recovering from synonymy and polysemy in text retrieval applications. However, since LSI ignores class labels of t...
Sutanu Chakraborti, Rahman Mukras, Robert Lothian,...
EXPERT
2008
134views more  EXPERT 2008»
13 years 7 months ago
Learning to Tag and Tagging to Learn: A Case Study on Wikipedia
Natural language technologies have been long envisioned to play a crucial role in transitioning from the current Web to a more "semantic" Web. If anything, the significa...
Peter Mika, Massimiliano Ciaramita, Hugo Zaragoza,...
NAACL
2003
13 years 9 months ago
Automatic Extraction of Semantic Networks from Text using Leximancer
Leximancer is a software system for performing conceptual analysis of text data in a largely language independent manner. The system is modelled on Content Analysis and provides u...
Andrew E. Smith