Presented at: Text Categorization via Ellipsoid Separation.
We present a new batch learning algorithm for text classification in the vector space of document representations. The algorithm uses ellipsoid separation in the feature space which leads to a semidefinite program. An approximation of the latent semantic feature extraction approach using Gram-Schmidt orthogonalization is used for the feature extraction. Preliminary results demonstrate some potential for the presented approach
|Type:||Conference item (UNSPECIFIED)|
|Event:||Text Categorization via Ellipsoid Separation|
|Keywords:||bag-of-words text representation, ellipsoid, feature extraction, Gram-Schmidt orthogonalization., latent semantic indexing, pattern separation, Semidefinite programming, Text categorization, text classification|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Computer Science
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