An Online Clustering Algorithm for Handling Evolving Data Streams with the Ability to Prevent Clusters' False Merging Using Adaptive Time Interval

Abstract

Online clustering of evolving data streams presents unique challenges, particularly the problem of false merging, where distinct clusters are incorrectly combined during temporal overlap. Existing buffer-based and density-based algorithms, such as BOCEDS and CEC-Merge, lack mechanisms to adaptively distinguish transient overlaps from genuine merging events. To address this, we propose BOCEDS-ATI—a Buffer-based Online Clustering for Evolving Data Streams with Adaptive Time Interval algorithm. The core innovation is the adaptive time interval mechanism, which dynamically adjusts merging decisions based on the temporal persistence and relative velocity of cluster interactions. This allows the model to recognize and prevent false merging in continuously evolving data streams. Experimental evaluation on multiple synthetic and real-world datasets demonstrates that BOCEDS-ATI achieves superior clustering accuracy and robustness to dynamic drift compared with state-of-the-art algorithms, while maintaining linear time complexity suitable for real-time applications. The results confirm that incorporating localized temporal adaptation significantly improves the reliability of online clustering in non-stationary environments.



Received: 17 July 2025 | Revised: 2 December 2025 | Accepted: 6 February 2026



Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.



Data Availability Statement

Data are available from the corresponding author upon reasonable request.



Author Contribution Statement

Redhwan Al-amri: Conceptualization, Methodology, Software, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization. Gamal Alkawsi: Validation, Project administration. Abdulnaser A. Hagar: Writing – review & editing. Luiz Fernando Capretz: Supervision, Funding acquisition.