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Effective Clustering for Large Datasets using Density-Based Clustering via Message Passing
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 187 - Number 48 |
| Year of Publication: 2025 |
| Authors: Siddharth Dixit |
10.5120/ijca2025925809
|
Siddharth Dixit . Effective Clustering for Large Datasets using Density-Based Clustering via Message Passing. International Journal of Computer Applications. 187, 48 ( Oct 2025), 28-39. DOI=10.5120/ijca2025925809
Abstract
Density-based clustering remains a significant area of research in data science, particularly given the increasing prevalence of high-dimensional datasets with varying densities. Many existing clustering approaches struggle to effectively handle datasets that contain regions of high density surrounded by sparse areas. This study introduces a novel clustering algorithm based on the concept of mutual K-nearest neighbor relationships, designed to overcome these limitations. The proposed method requires only a single input parameter, demonstrates strong performance on high-dimensional, density-based datasets, and is computationally efficient. Furthermore, the algorithm’s practical applications are illustrated through its potential to enhance search and retrieval processes within vector databases.
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