Introduction to Clustering Algorithms and Applications

TL;DR

This paper provides an overview of clustering algorithms and their applications across various disciplines, highlighting different methods and their relevance in real-world scenarios.

Contribution

It offers a comprehensive summary of key clustering techniques and their diverse applications, serving as an introductory resource.

Findings

Various clustering algorithms are summarized.

Clustering applications span multiple fields.

The importance of similarity measures in clustering.

Abstract

Data clustering is the process of identifying natural groupings or clusters within multidimensional data based on some similarity measure. Clustering is a fundamental process in many different disciplines. Hence, researchers from different fields are actively working on the clustering problem. This paper provides an overview of the different representative clustering methods. In addition, application of clustering in different field is briefly introduced.