Improving Performance of CluStream Algorithm

Abstract

The analysis of streaming data poses unique challenges due to the dynamic nature of the data and its potentially infinite size. Clustering algorithms designed for static datasets struggle to cope with streaming data. This research paper presents a comprehensive examination of the CluStream algorithm, a pioneering technique specifically developed for clustering data streams. The paper explores the key components of the algorithm, its underlying principles, advantages, and limitations. Additionally, it discusses the diverse applications of CluStream in various domains and highlights potential future research directions. This paper aims to offer researchers and practitioners a clear understanding of the CluStream algorithm and its implications for stream data clustering.