Article
Big Data and Recommender Systems
Novática: Journal of the Spanish Computer Scientist Association
(2016)
Abstract
This paper is an overview of recommender systems in the era of Big Data. We highlight prevailing recommendation algorithms and how they have been adapted to operate in parallel computing environments. These include traditional parallel computing environments, such as OpenMP and MPI, and also more recent distributed computing engines, such as MapReduce and Spark. Within the recommender systems context, we focus our discussion on scaling up two popular approaches, namely nearest neighbor and latent factor based recommendation.
Disciplines
Publication Date
October, 2016
Citation Information
David C. Anastasiu, Evangelia Christakopoulou, Shaden Smith, Mohit Sharma, et al.. "Big Data and Recommender Systems" Novática: Journal of the Spanish Computer Scientist Association Vol. 237 (2016) p. 39 - 45 ISSN: 2444-6629 Available at: http://works.bepress.com/david-anastasiu/4/