Data Stream Clustering

Data Stream Clustering analyzes the advantages as well as limitations of data stream algorithms and suggests potential areas for future research. It faces many challenges and have to satisfy constraints such as bounded memory, single-pass, real-time response, and concept-drift detection. It is usually studied as a streaming algorithm and the objective is, given a sequence of points, to construct a good clustering of the stream, using a small amount of memory and time.