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What is Clustering Streaming Data with Density Methods about?

This document proposes a new method for clustering streaming data using windows. It extends kernel density estimation to incorporate temporal information. The key ideas are: 1. It uses sliding windows that dynamically adjust their size and position to capture changing cluster structures over time. 2. The windows are incrementally recentered based on the mean of points within the window, weighted by both their distance to the center and temporal decay. 3. The windows periodically enlarge or contract the

Author

Nguyễn Dũng

Language

EN