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 …

Text summarization automatically produces a summary containing important sentences and
includes all relevant important information from the original document. One of the main …

Multi-document summarization (MDS) is an effective tool for information aggregation that
generates an informative and concise summary from a cluster of topic-related documents …

In this work, we propose a novel method for training neural networks to perform single-
document extractive summarization without heuristically-generated extractive labels. We call …

In this paper, we propose DeepSumm, a novel method based on topic modeling and word
embeddings for the extractive summarization of single documents. Recent summarization …

Extractive text summarization involves selecting and combining key sentences directly from
the original text, rather than generating new content. While various methods, both statistical …

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 …

In this paper, three methods of extracting single document summary by combining
supervised learning with unsupervised learning are proposed. The purpose of these three …

In this paper, an abstractive Arabic text summarization model that is based on sequence-to-
sequence recurrent neural networks is proposed. It consists of a multilayer encoder and …

With the rise in the amount of textual data over the internet, the demand for summarizing it in
a short, readable, easy-to-understand form has increased. Much of the research is being …