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

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 …

Swarm intelligence (SI) is a research field which has recently attracted the attention of
several scientific communities. An SI approach tries to characterize the collective behavior of …

In machine learning and data mining, feature selection (FS) is one of the most important
tasks required to select the most relevant instances from a dataset. In other words, FS is …

The continually developing Internet generates a considerable amount of text data. When
attempting to extract general topics or themes from a massive corpus of documents, dealing …

Text clustering is an efficient analysis technique used in the domain of the text mining to
arrange a huge of unorganized text documents into a subset of coherent clusters. Where, the …

Text Document Clustering (TDC) is a challenging optimization problem in unsupervised
machine learning and text mining. The Salp Swarm Algorithm (SSA) has been found to be …

This chapter provides an in-depth overview of the metaheuristic optimization algorithms
used in the domain of document/text clustering as well as a description of their main …

Bio-inspired intrusion detection solutions provide better detection accuracy than
conventional solutions in securing cyberspace. However, existing bio-inspired anomaly …

Event Detection (ED) is a study area that attracts the attention of decision-makers from
various disciplines in order to help them in taking the right decision. ED has been examined …