We introduce a Bayesian model, BayesANIL, that is capable of estimating uncertainties associated with the labeling process. Given a labeled or partially labeled training corpus of...
Evaluating text fragments for positive and negative subjective expressions and their strength can be important in applications such as single- or multi- document summarization, do...
A major difficulty of supervised approaches for text classification is that they require a great number of training instances in order to construct an accurate classifier. This pap...
Classification is a well-established operation in text mining. Given a set of labels A and a set DA of training documents tagged with these labels, a classifier learns to assign l...
Single-Class Classification (SCC) seeks to distinguish one class of data from the universal set of multiple classes. We present a new SCC algorithm that efficiently computes an ac...