The main objective of feature selection is to improve learning performance by selecting
concise and informative feature subsets, which presents a challenging task for machine …

This paper presents a comprehensive survey of the meta-heuristic optimization algorithms
on the text clustering applications and highlights its main procedures. These Artificial …

In this paper, a novel text clustering method, improved krill herd algorithm with a hybrid
function, called MMKHA, is proposed as an efficient clustering way to obtain promising and …

Text clustering is one of the efficient unsupervised learning techniques used to partition a
huge number of text documents into a subset of clusters. In which, each cluster contains …

Effective task scheduling is recognized as one of the main critical challenges in cloud
computing; it is an essential step for effectively exploiting cloud computing resources, as …

Text Summarization is the process of creating a summary of a certain document that
contains the most important information of the original one, the purpose of it is to get a …

This paper thoroughly introduces a comprehensive review of the so-called Dragonfly
algorithm (DA) and highlights its main characteristics. DA is considered one of the promising …

In this paper, the economic load dispatch (ELD) problem which is an important problem in
electrical engineering is tackled using a hybrid sine cosine algorithm (SCA) in a form of …

The symbiotic organism search (SOS) is a recently proposed metaheuristic optimization
algorithm that simulates the symbiotic interaction strategies adopted by organisms to survive …

Grouping problems are a special type of combinatorial optimization problems that have
gained great relevance because of their numerous real-world applications. The solution …