As an emerging field that aims to bridge the gap between human activities and computing
systems, human-centered computing (HCC) in cloud, edge, fog has had a huge impact on …

The recent advancements in big data and natural language processing (NLP) have
necessitated proficient text mining (TM) schemes that can interpret and analyze voluminous …

Most current genotype imputation methods are reference-based, which posed several
challenges to users, such as high computational costs and reference panel inaccessibility …

Summarizing lengthy text involves distilling crucial information into a concise form by
covering the key events in the source text. Previous researchers mostly explored the …

Text summarization is a technique that converts large text into shorter ones by kee** its
important information. Most of the available summarizers, summarize English language text …

Text summarization is the extraction of significant knowledge from files without losing its
original content. Various linguistic, statistic, and rule-based techniques have been …

In today's digital era, the need for succinct yet insightful representation of vast amounts of
information has never been greater. Text summarization stands at the forefront of this …

Abstract text summarization is a classic sequence-to-sequence natural language generation
task. In order to improve the quality of unsupervised abstract text summarization in …

Text summarization is the process of employing a system to shorten a document or a
collection of documents into brief paragraphs or sentences using various approaches. This …

Automatic text summarization plays a very important role in text retrieval. But, very little
interest and attention in Hindi text summarization; motivates to develop a technique for …