We propose and evaluate a family of methods for converting classifier learning algorithms and classification theory into cost-sensitive algorithms and theory. The proposed conve...
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and com...
We present Sentiment Analyzer (SA) that extracts sentiment (or opinion) about a subject from online text documents. Instead of classifying the sentiment of an entire document abou...
Jeonghee Yi, Tetsuya Nasukawa, Razvan C. Bunescu, ...
Previous works on automatic query clustering most generate a flat, un-nested partition of query terms. In this work, we are pursuing to organize query terms into a hierarchical s...
Presently, inductive learning is still performed in a frustrating batch process. The user has little interaction with the system and no control over the final accuracy and traini...
Wei Fan, Haixun Wang, Philip S. Yu, Shaw-hwa Lo, S...