Call For Paper Volume:4 Issue:6 Jun'2017

Collaborative Based Clustering On Big Data Using HACE Theorem

Publication Date : 31/03/2015

Author(s) :

N.SARAVANAN , Chinnadurai.S , Dinesh Raj.R , Suguna.G.

Volume/Issue :
Volume 2
Issue 3
(03 - 2015)

Abstract :

— Currently, the large amount of data produced by many organizations is outpacing their storage ability. The management of such huge amount of data is quite expensive due to the requirements of high storage capacity and qualified personnel. So the Big Data is used to describe these types of massive volume of both structured and unstructured data that is so large that it's difficult to process using traditional database and software techniques. Big Data has the potential to help companies improve operations and make faster, more intelligent decisions. In many E-Commerce sites, Recommender Systems (RS), which provide personalized recommendation from among a large number of items, are recently introduced. Collaborative clustering is one of the most successful algorithms which provide recommendations using ratings of users on items. A CLUBCF (Clustering-Based Collaborative Filtering) approach is a service and its aims at gathering similar services in the same clusters to the recommend services collaborativelyThe HACE theorem is a data-driven model and it involves demand-driven aggregation of information sources, mining and analysis, user interest modeling and security and privacy considerations. At the filtering stage HACE theorem is to be applied for efficient process. At last, several important experiments are performed to verify the availability of the approach Keywords— Big Data, CLUBCF,HACE Theorem,Recommender System(RS)

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Collaborative Based Clustering On Big Data Using HACE Theorem

March 3, 2015