In this paper, we introduce a method for categorizing digital items according to their topic, only relying on the document's metadata, such as author name and title informati...
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...
Abstract. We describe a semantic clustering method designed to address shortcomings in the common bag-of-words document representation for functional semantic classification tasks....
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...
In this paper, we present the main features of a text mining based search engine for the UK Educational Evidence Portal available at the UK National Centre for Text Mining (NaCTeM...
Sophia Ananiadou, John McNaught, James Thomas, Mar...