Text classification using a small labeled set and a large unlabeled data is seen as a promising technique to reduce the labor-intensive and time consuming effort of labeling traini...
Abstract. In text classification (TC) and other tasks involving supervised learning, labelled data may be scarce or expensive to obtain; strategies are thus needed for maximizing t...
Spreadsheets applications allow data to be stored with low development overheads, but also with low data quality. Reporting on data from such sources is difficult using traditiona...
Text classification is the process of classifying documents into predefined categories based on their content. Existing supervised learning algorithms to automatically classify te...
In recent years, active learning methods based on experimental design achieve state-of-the-art performance in text classification applications. Although these methods can exploit ...