Abstract Automatic Text Summarization (ATS) is becoming much more important because of
the huge amount of textual content that grows exponentially on the Internet and the various …

As information is available in abundance for every topic on internet, condensing the
important information in the form of summary would benefit a number of users. Hence, there …

Nowadays we see huge amount of information is available on both, online and offline
sources. For single topic we see hundreds of articles are available, containing vast amount …

This paper presents an efficient graph-enhanced approach to multi-document
summarization (MDS) with an encoder-decoder Transformer model. This model is based on …

Humans must easily handle the vast amounts of data being generated by the revolution of
information technology. Thus, Automatic Text summarization has been applied to various …

Abstract Background and Objective Capturing the context of text is a challenging task in
biomedical text summarization. The objective of this research is to show how contextualized …

The vast amounts of data being collected and analyzed have led to invaluable source of
information, which needs to be easily handled by humans. Automatic Text Summarization …

Extractive multi-document summarization (MDS) is the process of automatically summarizing
a collection of documents by ranking sentences according to their importance and …

In this paper, we propose Ranksum, an approach for extractive text summarization of single
documents based on the rank fusion of four multi-dimensional sentence features extracted …

Due to the exponential growth of online information, the ability to efficiently extract the most
informative content and target specific information without extensive reading is becoming …