Traditionally, text classifiers are built from labeled training examples. Labeling is usually done manually by human experts (or the users), which is a labor intensive and time co...
In traditional text classification, a classifier is built using labeled training documents of every class. This paper studies a different problem. Given a set P of documents of a ...
In automated text categorization, given a small number of labeled documents, it is very challenging, if not impossible, to build a reliable classifier that is able to achieve high...
Zenglin Xu, Rong Jin, Kaizhu Huang, Michael R. Lyu...
In this paper we present a new approach to classifying radiographs, which is the first important task of the IRMA system. Given an image, we compute posterior probabilities for ea...
Various relevance feedback algorithms have been proposed in recent years in the area of content-based image retrieval. This paper gives a brief review and analysis on existing tec...