In this paper, we survey text summarization (TS) datasets in Indian languages (ILs), which
are also low-resource languages (LRLs). We seek to answer one primary question—is the …

Manual summarization of large documents of texts is tedious and error prone. Also, the
results in such kind of summarization may lead to different results for a particular document …

Propelled by the advancements in the field of natural language processing, generating
summaries of long texts using various NLP tools and techniques has always been a subject …

Text summarization is a process which defines summary as text which reflects the main and
important sentences from the original text and preserving its information content and overall …

In natural language processing, it is important that the context and the meaning of words are
retained while also ensuring the efficacy of the data modelling process. During human-to …

The internet is comprised of web pages, news articles, status updates, blogs and much
more. It is difficult to navigate through this data as it is unstructured and usually discursive …

Automatic text summarization is an essential part of Natural language processing (NLP), a
subpart of the Artificial Intelligence domain. Widespread usage of text summarization is due …

The text summarization is a technique where the original large text is condensed into
smaller version without changing its abstract meaning. The text summarization is done on …

Extracting/abstracting the condensed form of original text document by retaining its
information and complete meaning is known as text summarization. The creation of manual …

Automatic summarization is the process of generating condensed version of text. A wide
variety of data is available on the web, and to make reading quick and efficient for people …