Probabilistic topic models have become popular as methods for dimensionality reduction in collections of text documents or images. These models are usually treated as generative m...
This paper introduces an information retrieval based approach for automating the detection and classification of non-functional requirements (NFRs). Early detection of NFRs is use...
Jane Cleland-Huang, Raffaella Settimi, Xuchang Zou...
Text classification is the process of classifying documents into predefined categories based on their content. Existing supervised learning algorithms to automatically classify te...
Abstract We address the problem of indexing broadcast audiovisual documents (such as films, news). Starting from a collection of so-called shots, we aim at building automatically h...
Standard Machine Learning approaches to text classification use the bag-of-words representation of documents to deceive the classification target function. Typical linguistic stru...