The automatic text summarization (ATS) task consists in automatically synthesizing a
document to provide a condensed version of it. Creating a summary requires not only …

This study proposes a language and domain independent approach for automatic extractive
text summarization (EATS) tasks, which is based on a clustering scheme supported by a …

The extractive text summarization (ETS) method for finding the salient information from a text
automatically uses the exact sentences from the source text. In this article, we answer the …

In everyday life, multi-document summarization (MDS) methods are becoming tremendous
attention in different fields, especially for online documents, because this online document …

With the exponential proliferation of digital documents, there arises a pressing need for
automated document summarization (ADS). Summarization, a compression technique …

Abstract Multi-Document Text Summarization (MDTS) consists of generating an abstract
from a group of two or more number of documents that represent only the most important …

The textual information has accelerated growth in the most spoken languages by native
Internet users, such as Chinese, Spanish, English, Arabic, Hindi, Portuguese, Bengali …

Abstract The task of Extractive Multi-Document Text Summarization (EMDTS) aims at
building a short summary with essential information from a collection of documents. In this …

The main problem for generating an extractive automatic text summary (EATS) is to detect
the key themes of a text. For this task, unsupervised approaches cluster the sentences of the …

For multi-document text summarization, text features are fundamental because they
determine the importance of each sentence from source documents. Therefore, selected …