Discourse theories claim that text gets meaning in context. Most summarization systems do not take advantage of this. They assess the relevance of each passage individually rather than modeling the way context affects the relevance of passages. This paper presents a framework for graph-based summarization in order to model relations in text, so that the passages can be viewed in a broader conte...

Automatic text summarization helps the user to quickly understand large volumes of information. We present a languageand domain-independent statistical-based method for single-document extractive summarization, i.e., to produce a text summary by extracting some sentences from the given text. We show experimentally that words that are parts of bigrams that repeat more than once in the text are g...

Summarization of spoken conversations is a challenging task, since it requires deep understanding of dialogs. Abstractive summarization techniques rely on linking the summary sentences to sets of original conversation sentences, i.e. communities. Unfortunately, such linking information is rarely available or requires trained annotators. We propose and experiment automatic community creation usi...

Due to the overabundance of textual information on-line, automatic text summarization [Saggion and Poibeau, 2013], the reduction of a text to its essential content, is fundamental for information systems dealing with textual content. In recent years text summarization research has intensified with well known evaluation programmes promoting the interest in the area. Comparison of different summa...

We propose a new, ambitious framework for abstractive summarization, which aims at selecting the content of a summary not from sentences, but from an abstract representation of the source documents. This abstract representation relies on the concept of Information Items (INIT), which we define as the smallest element of coherent information in a text or a sentence. Our framework differs from pr...

While automatic text summarization is an area that has received a great deal of attention in recent research, the problem of efficiency in this task has not been frequently addressed. When considering the size and quantity of documents available on the Internet and from other sources, the need for a highly efficient tool that produces usable summaries is clear. We present a linear time algorith...