Title :
Suggested techniques for clustering and mining of data streams
Author :
Anuradha, G. ; Roy, Bidisha
Author_Institution :
Dept. of Comput. Eng., St. Francis Inst. of Technol., Mumbai, India
Abstract :
The buzz word in research is Big Data. Big Data gets characterized by 5 V´s: Volume, Velocity, Variety, Veracity and Value of data. Volume in order of penta bytes, velocity which refers to click stream data in various domains, variety comprising of heterogeneous data, veracity indicating the cleanliness of data and value emphasizing on the return on investment for companies who invest in Big Data technologies. This Big Data is better modeled not as persistent tables but in the form of transient data streams which need different clustering and mining techniques to be effectively processed and managed. In this paper some suggestions on online learning through clustering and mining of stream data are presented.
Keywords :
Big Data; data mining; pattern clustering; Big Data technology; buzz word; data stream clustering technique; data stream mining technique; data value; data variety; data velocity; data veracity; data volume; heterogeneous data; online learning; return on investment; transient data streams; Algorithm design and analysis; Big data; Classification algorithms; Clustering algorithms; Data mining; Heuristic algorithms; Prediction algorithms; Big Data; Clustering; Data Streams; Mining;
Conference_Titel :
Circuits, Systems, Communication and Information Technology Applications (CSCITA), 2014 International Conference on
Conference_Location :
Mumbai
DOI :
10.1109/CSCITA.2014.6839270
