In this paper, we investigate how modeling content structure can benefit text analysis applications such as extractive summarization and sentiment analysis. This follows the lingu...
Supervised methods for extractive speech summarization require a large training set. Summary annotation is often expensive and time consuming. In this paper, we exploit semisuperv...
We describe iNeATS – an interactive multi-document summarization system that integrates a state-of-the-art summarization engine with an advanced user interface. Three main goals...
Abstract. Extractive text summarization is the process of selecting relevant sentences from a collection of documents, perhaps only a single document, and arranging such sentences ...