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 …

In recent years, multi-objective optimization (MOO) techniques have become popular due to
their potentiality in solving a wide variety of real-world problems, including bioinformatics …

Text document clustering is to divide textual contents into clusters or groups. It received wide
attention due to the vast amount of daily data from the Web. In the last decade, Meta …

Automatic text summarization schemes are indeed helpful for glancing briefly at the text
document. With this motivation, we introduce here a two-stage hybrid model for text …

A multi-objective forensic-based investigation (MOFBI) algorithm is developed to solve
engineering optimization problems with multiple objectives. In the proposed algorithm, a …

The automatic generation of a text summary is a task of generating a short summary for a
relatively long text document by capturing its key information. In the past, supervised …

Featured Application A graph-based technique tested on a benchmark dataset and
augmented by machine learning techniques to provide a concise, informative, and …

The central challenge in Automatic Text Summarization (ATS) involves efficiently generating
machine-generated text summaries through optimization algorithms. An ATS is a critical …

Due to the exponential overflow of textual information in various fields of knowledge and on
the internet, it is very challenging to extract important information or to generate a summary …

As the world is progressing faster, to compete with the demand, the need for proficient
computing technology has increased, resulting in huge volumes of data. Consequently, the …