Text summarization is the process of condensing a long text into a shorter version by
maintaining the key information and its meaning. Automatic text summarization can save …

With the rapid growth of social media platforms, digitization of official records, and digital
publication of articles, books, magazines, and newspapers, lots of data are generated every …

With the evolution of the Internet and multimedia technology, the amount of text data has
increased exponentially. This text volume is a precious source of information and knowledge …

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 …

Abstract Automatic Text Summarization (ATS) is an essential field in natural language
processing that attempts to condense large text documents so that users can assimilate …

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

Nowadays, voluminous unstructured data is steaming on the Web/social media. It is not easy
for individuals to find relevant information quickly from such a vast unstructured corpus. Text …

The task of summarization can be categorized into two methods, extractive and abstractive.
Extractive summarization selects the salient sentences from the original document to form a …

Searching the Internet for a certain topic can become a daunting task because users cannot
read and comprehend all the resulting texts. Automatic Text summarization (ATS) in this …

We propose a novel methodology for extractive, generic summarization of text documents.
The Maximum Independent Set, which has not been used previously in any summarization …