Literature Review Open Access

Advances in Document Clustering with Evolutionary-Based Algorithms

Sarmad Makki1, Razali Yaakob2, Norwati Mustapha2 and Hamidah Ibrahim2
  • 1 College of Science, University of Baghdad, 10071 Baghdad, Iraq
  • 2 Faculty of Computer Science and Information Technology, University Putra Malaysia, 43400 Selangor, Malaysia


Document clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Formerly, a number of conventional algorithms had been applied to perform document clustering. There are current endeavors to enhance clustering performance by employing evolutionary algorithms. Thus, such endeavors became an emerging topic gaining more attention in recent years. The aim of this paper is to present an up-to-date and self-contained review fully devoted to document clustering via evolutionary algorithms. It firstly provides a comprehensive inspection to the document clustering model revealing its various components with its related concepts. Then it shows and analyzes the principle research work in this topic. Finally, it compiles and classifies various objective functions, the core of the evolutionary algorithms, from the related collection of research papers. The paper ends up by addressing some important issues and challenges that can be subject of future work.

American Journal of Applied Sciences
Volume 12 No. 10, 2015, 689-708


Submitted On: 20 January 2015 Published On: 20 October 2015

How to Cite: Makki, S., Yaakob, R., Mustapha, N. & Ibrahim, H. (2015). Advances in Document Clustering with Evolutionary-Based Algorithms. American Journal of Applied Sciences, 12(10), 689-708.

  • 2 Citations



  • Text Document Clustering
  • Hypertext Clustering
  • Evolutionary Algorithms
  • Genetic Algorithms
  • Text Dimensional Reduction