Zeynep Hilal Kilimci

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—It has been shown that Latent Semantic Indexing (LSI) takes advantage of implicit higher-order (or latent) structure in the association of terms and documents. Higher-order relations in LSI capture " latent semantics ". Inspired by this, a novel Bayesian framework for classification named Higher Order Naïve Bayes (HONB), which can explicitly make use of(More)
It is known that latent semantic indexing (LSI) takes advantage of implicit higher-order (or latent) structure in the association of terms and documents. Higher-order relations in LSI capture “latent semantics”. These findings have inspired a novel Bayesian framework for classification named Higher-Order Naive Bayes (HONB), which was introduced previously,(More)
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