Advances in document clustering with evolutionary-based algorithms

• Main Authors: Makki, Sarmad, Yaakob, Razali, Mustapha, Norwati, Ibrahim, Hamidah
• Format: Article
• Language: English
• Published: Science Publications 2015
• Online Access: http://psasir.upm.edu.my/id/eprint/43671/1/Advances%20in%20Document%20Clustering%20with%20Evolutionary-Based.pdf; http://psasir.upm.edu.my/id/eprint/43671/; http://thescipub.com/abstract/10.3844/ajassp.2015.689.708
• Institution: Universiti Putra Malaysia

Document clustering is the process of organizing a particularelectronic corpus of documents into subgroups of similar text features.Formerly, a number of conventional algorithms had been applied to performdocument clustering. There are current endeavors to enhance clusteringperformance by employing evolutionary algorithms. Thus, such endeavors becamean emerging topic gaining more attention in recent years. The aim of this paperis to present an up-to-date and self-contained review fully devoted to documentclustering via evolutionary algorithms. Itfirstly provides a comprehensive inspection to the document clustering model revealingits various components with its related concepts. Then it shows and analyzesthe principle research work in this topic. Finally, it compiles and classifiesvarious objective functions, the core of the evolutionary algorithms, from therelated collection of research papers. The paper ends up by addressing someimportant issues and challenges that can be subject of future work.