BFSMpR:A BFS Graph based Recommendation System using Map Reduce

Abstract

Nowadays, Many associations, organizations and analysts need to manage huge datasets (i.e. Terabytes or even Petabytes). A well-known information filtering algorithm for dealing with such large datasets in an effective way is Hadoop Map Reduce. These large size datasets are regularly known to as graphs by many frameworks of current intrigue (i.e. Web, informal organization). A key element of the graph based recommendation system is that they depend upon the neighbor’s interest by taking minimum distance into account. Generally recent day proposal frameworks utilize complex strategy to give recommend to every user. This paper introduced an alternate approach to give suggestions to users in used of an un-weighted graph using a Hadoop iterative MapReduce approach for the execution.)