… 3.1 Clustering in Small Space Data stream algorithms must not have large space require…
will be to show that clustering can be carried out in a small space (n for n data points, and 0 < < 1…

… practice, it is instructive to keep them in mind when designing algorithms for clustering data
streams… -of-the-art algorithms for clustering data streams. Surveys on this subject have been …

… some difficulties in data stream clustering. Most data stream applications are high …
Furthermore concept drift is nature of data stream and should be managed by new methods. …

… In order to appreciate the difficulty that arises in clustering a data stream, we describe the
non-streaming algorithms first. We begin with the FARTHEST POINT clustering algorithm which …

… -the-art data stream mining algorithms with a focus on clustering and classification because
of … clustering and classification of data stream as they are the two most frequent forms of data …

… effective data stream clustering algorithm is crucial. This paper reviews the development
and trend of data stream clustering and analyzes typical data stream clustering algorithms …

… clustering of multiple and parallel data streams. Our study should be differentiated from some
previous studies on clustering stream data [19… for clustering multiple data streams based on …

… of data may pose different challenges to data stream clustering. … representations of the clusters
effectively without increasing the … algorithms for clustering data streams. High dimensional …

… of correlation clustering in the dynamic data stream model. The stream consists of updates to
… different clusters whereas the end-points of positive-weight edges are typically in the same …

… streams, time window models and outlier detection. We comprehensively review recent
data stream clustering algorithms and analyze them in terms of the base clustering technique, …