Publication Type:

Journal Article

Authors:

Sathyadevan, S.a; Hariram, S.a; Antony, A.b; Mahith, V.P.b

Source:

International Journal of Applied Engineering Research, Research India Publications, Volume 10, Number 9, p.22133-22144 (2015)

URL:

http://www.scopus.com/inward/record.url?eid=2-s2.0-84934917383&partnerID=40&md5=e6325dacc4783828c599ca829502e74a

Abstract:

Real world data is processed in multiple servers which constitutes a huge collection of data that causes the browser to crash at regular interval of time. The Aggregation have been done to those data that are generated from various sources like log files, video, text, image etc.This paper combines the fusion of hierarchical clustering with Map-reduce which indicates the grouping of same type of data and reducing it in to key-value pairs,this classification makes the processing and retrieval of real time data easy. Visualization of these data increases the efficiency for user to analyze it.The research results provide a better way to aggregate huge amount of data with high efficiency. © Research India Publications.

Notes:

cited By 0

Cite this Research Publication

Sa Sathyadevan, Hariram, Sa, Antony, Ab, and Mahith, V. Pb, “Fast approximate aggregation algorithms for effective browser visualization using similarity heuristics”, International Journal of Applied Engineering Research, vol. 10, pp. 22133-22144, 2015.