TY - JOUR
AB - International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8 Issue-11, September 2019 Data Stream Clustering Algorithms: Challenges and Future Directions G. Sunitha, C. Jaswitha Abstract: In the fast growing world applications are generating form data streams, just to name a few [1]. The datasets data in enormous volumes called data streams. Data stream is obtained from these applications are huge to fit in main imaginably large, continual, rapid flow of information and in memory hence moved to external storage device. Based on data mining the important tool is called clustering, hence data the above reason, it is expensive to perform random access on stream clustering (DSC) can be said as active research area. the datasets; hence the accessing method is to provide regular Recent attention of data stream clustering is through the scans of the data to achieve performance efficiency. applications that contain large amounts of streaming data. Data stream clustering is used in many areas such as weather Creating data clusters with the help of mining data streams forecasting, financial transactions, website analysis, sensor eventually be a provocation because of several reasons: (i) network monitoring, e-business, telephone records and single-scan clustering: clustering of data need 
TI - Data Stream Clustering Algorithms: Challenges and Future Directions
JF - Regular Issue
DO - 10.35940/ijitee.k1990.0981119
DA - 2019-09-10
UR - https://www.deepdyve.com/lp/unpaywall/data-stream-clustering-algorithms-challenges-and-future-directions-dxa1WZpaAO
DP - DeepDyve
ER -