: Discovering interesting patterns or substructures in data streams is an important challenge in data mining. Clustering algorithms are very often applied to identify single substr...
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 ...
Streaming data analysis has recently attracted attention in numerous applications including telephone records, web documents and clickstreams. For such analysis, single-pass algor...
Liadan O'Callaghan, Adam Meyerson, Rajeev Motwani,...
This paper describes one of the first attempts to model the temporal structure of massive data streams in real-time using data stream clustering. Recently, many data stream clust...
Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...