Semi-naive Bayesian classifiers seek to retain the numerous strengths of naive Bayes while reducing error by weakening the attribute independence assumption. Backwards Sequential ...
As text corpora become larger, tradeoffs between speed and accuracy become critical: slow but accurate methods may not complete in a practical amount of time. In order to make the...
Lawrence Shih, Jason D. Rennie, Yu-Han Chang, Davi...
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Taxonomies of the Web typically have hundreds of thousands of categories and skewed category distribution over documents. It is not clear whether existing text classification tech...
Tie-Yan Liu, Yiming Yang, Hao Wan, Qian Zhou, Bin ...
This work aims to provide a page segmentation algorithm which uses both visual and content information to extract the semantic structure of a web page. The visual information is u...