This paper focuses on the problem of real-time clustering on streaming data in computation-intensive and high-dynamics tasks, through a framework Ocean.

This paper focuses on the problem of real-time clustering on streaming data in computation-intensive and high-dynamics tasks, through a framework Ocean, ...

This paper focuses on the problem of real-time clustering on streaming data in computation-intensive and high- dynamics tasks, through a framework Ocean, ...

May 13, 2024 · Ocean: Online Clustering and Evolution Analysis for Dynamic Streaming Data. Chunhui Feng 1. ,. Junhua Fang 1. ,. Yue Xia 1. ,. Pingfu Chao 1.

In this paper, we propose an online clustering algorithm that considers the temporal proximity of observations as well as their spatial proximity to identify ...

We track the evolution of clusters by monitoring the changes of density mountains. We further provide efficient data structures and filtering schemes to ensure ...

This paper proposes a generally dynamic approach to clustering in high-velocity dynamic scenarios, where the objects are continuously updated, inserted, ...

We introduce a dynamic radius threshold for each micro-cluster in the online phase, allowing for fine adaptation to statistical changes in the data stream ...

This paper proposes an active learning algorithm based on clustering, which improves the online semi-supervised learning algorithm.

Ocean: Online Clustering and Evolution Analysis for Dynamic Streaming Data. Conference Paper. May 2024. Chunhui Feng · Xiaofang Zhou · Junhua Fang · Yue Xia.