Existing density-based data stream clustering algorithms use a two-phase scheme approach consisting of an online phase, in which raw data is processed to gather summary statistics...
Agostino Forestiero, Clara Pizzuti, Giandomenico S...
Monitoring cluster evolution in data streams is a major research topic in data streams mining. Previous clustering methods for evolving data streams focus on global clustering res...
Liang Tang, Chang-jie Tang, Lei Duan, Chuan Li, Ye...
As organizations accumulate data over time, the problem of tracking how patterns evolve becomes important. In this paper, we present an algorithm to track the evolution of cluster...
Stream data is common in many applications, e.g., stock quotes, merchandize sales record, system logs, etc.. It is of great importance to analyze these stream data. As one of the ...
Data stream clustering has emerged as a challenging and interesting problem over the past few years. Due to the evolving nature, and one-pass restriction imposed by the data strea...