Hybrid clustering analysis using improved krill herd algorithm

• Published in: Applied intelligence (Dordrecht, Netherlands) Vol. 48; no. 11; pp. 4047 - 4071
• Main Authors: Abualigah, Laith Mohammad, Khader, Ahamad Tajudin, Hanandeh, Essam Said
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.11.2018; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Cluster analysis; Clustering; Computer Science; Datasets; Krill; Machines; Manufacturing; Mechanical Engineering; Optimization; Processes; Searching; Improved krill herd algorithm; Text document clustering; Hybrid function; Optimization problem; Tuning parameters

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 precise results in this domain. Krill herd is a new swarm-based optimization algorithm that imitates the behavior of a...