Procesamiento distribuido aplicando similitud de coseno para la correlación de Big Data en Hadoop (Distributed processing using cosine similarity for mapping Big Data in Hadoop)

Andrés Felipe Rojas Hernández (afrojash@correo.udistrital.edu.co)1, Nancy Yaneth Gelvez García (nygelvezg@udistrital.edu.co)1


1Universidad Distrital Francisco José de Caldas

This paper appears in: Revista IEEE América Latina

Publication Date: June 2016
Volume: 14,   Issue: 6 
ISSN: 1548-0992


Abstract:
The analysis of big data is an issue that has become very important in recent years. The use of algorithms for processing big data that have generated as a result valuable information to organizations can be considered one of the biggest developments and most important lines of work today. This paper aims to show results in implementing cosine similarity for mapping big data in a flat database. For this purpose the information from movie ratings will be used, so it will result in a recommendation of a movie highly related to another. If the information used for testing is considered real, these results could be useful for the development of a recommendation system for products and services from an organization which has as well the records of their customers' ratings.

Index Terms:
Big Data, Haddop, Cluster, Cosine similarity   


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