Recent Trends in Incremental Clustering: A Review
Neha Chopade, Jitendra Sheetlani · IOSR Journal of Computer Engineering · 2017
This paper presents a review on recent trends in incremental clustering algorithms.It tries to focus on both clustering based on similarity measure and clustering not based on similarity measure.In this context, the paper is devoted to various typical incremental clustering algorithms.Mainly optimization, genetic and fuzzy approaches of these algorithms is covered in the paper.The paper is original with respect to one aspect that is, it provides a complete overview that is fully devoted to evolutionary algorithms for incremental clustering.A number of references are provided that describe applications of evolutionary algorithms for incremental clustering in different domains, such as human activity detection, online fault detection, information security, track an object consistently throughout the network solving boundary problem etc.