Automatic Text Summarization

. A large amount of on-line information and lengthiness information can’t fit for the mobile devices. In order to save this problem, we propose a method which collects original news …...

Lexical Chains are powerful representa- tions of documents. In particular, they have successfully been used in the field of Automatic Text Summarization. How- ever, until now, Lexical Chaining algo- rithms …...

This paper analyzes the topic identification stage of single-document automatic text sum- marization across four different domains, con- sisting of newswire, literary, scientific and le- gal documents. We present a …...

AbstractAutomatic text summarization, the reduction of a text to its essential content is fundamental for an on-line information society. Although many summarization algorithms exist, there are few tools or infrastructures …...

AbstractWe present results from an eye tracking study of automatic text summarization. Automatic text summarization is a growing field due to the modern world’s Internet based society, but to automatically …...

Automatic text summarization is widely regarded as the highly difficult problem, partially because of the lack of large text summarization data set. Due to the great challenge of constructing the …...

AbstractTeaching large classes remains a great challenge, primarily because it is difficult to attend to all the student needs in a timely manner. Automatic text summarization systems can be leveraged …...

Most automatic text summarization sys- tems proposed to date rely on centrality and structural features as indicators for information importance. In this paper, we argue that these features cannot reli- …...

AbstractThe task of automatic text summarization is to generate a short text that summarizes the most important information in a given set of documents. Sentence regression is an emerging branch …...

AbstractAlthough automatic text summarization (ATS) has been researched for several decades, the application of graph neural networks (GNNs) to this task started relatively recently. In this survey we provide an …...

AbstractSocial media posts provide a compelling, yet challenging source of data of diverse perspectives from many socially salient groups. Automatic text summarization algorithms make this data accessible at scale by …...

AbstractThe distribution of fake news is not a new but a rapidly growing problem. The shift to news consumption via social media has been one of the drivers for the …...

AbstractIn this paper, we evaluate several Transformer-based language models for Icelandic on four downstream tasks: Part-of-Speech tagging, Named Entity Recognition. Dependency Parsing, and Automatic Text Summarization. We pre-train four types …...