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COLING
1996
15 years 8 months ago
FeasPar - A Feature Structure Parser Learning to Parse Spoken Language
We describe and experimentally evaluate a system, FeasPar, that learns parsing spontaneous speech. To train and run FeasPar (Feature Structure Parser), only limited handmodeled kn...
Finn Dag Buø, Alex Waibel
BDA
2007
15 years 8 months ago
Hyperplane Queries in a Feature-Space M-tree for Speeding up Active Learning
In content-based retrieval, relevance feedback (RF) is a noticeable method for reducing the “semantic gap” between the low-level features describing the content and the usually...
Michel Crucianu, Daniel Estevez, Vincent Oria, Jea...
MTA
2006
173views more  MTA 2006»
15 years 6 months ago
Active learning in very large databases
Abstract. Query-by-example and query-by-keyword both suffer from the problem of "aliasing," meaning that example-images and keywords potentially have variable interpretat...
Navneet Panda, Kingshy Goh, Edward Y. Chang
TKDE
2008
148views more  TKDE 2008»
15 years 6 months ago
Semisupervised Clustering with Metric Learning using Relative Comparisons
Semisupervised clustering algorithms partition a given data set using limited supervision from the user. The success of these algorithms depends on the type of supervision and also...
Nimit Kumar, Krishna Kummamuru
IJCIS
2000
40views more  IJCIS 2000»
15 years 6 months ago
Lessons Learned from Applying AI to the Web
Ontobroker applies Artificial Intelligence techniques to improve access to heterogeneous, distributed and semistructured information sources as they are presented in the World Wid...
Dieter Fensel, Jürgen Angele, Stefan Decker, ...