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RNTI

MODULAD
Development of a distributed recommender system using the Hadoop Framework
In EGC 2012, vol. RNTI-E-23, pp.275-280
Résumé
Producing high quality recommendations has become a challenge in
the recent years. Indeed, the growth in the quantity of data involved in the recommendation
process pose some scalability and effectiveness problems. These
issues have encouraged the research of new technologies. Instead of developing
a new recommender system we improve an already existing method. A distributed
framework was considered based on the known quality and simplicity of
the MapReduce project. The Hadoop Open Source project played a fundamental
role in this research. It undoubtedly encouraged and facilitated the construction
of our application, supplying all tools needed. Our main goal in this research was
to prove that building a distributed recommender system was not only possible,
but simple and productive.