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Fast approximate aggregation algorithms for effective browser visualization using similarity heuristics

Publication Type : Conference Paper

Thematic Areas : Amrita Center for Cybersecurity Systems and Networks

Publisher : International Journal of Applied Engineering Research

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

Campus : Amritapuri

School : Centre for Cybersecurity Systems and Networks, School of Engineering

Center : Cyber Security

Department : cyber Security

Year : 2015

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.

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

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