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Publication Type : Conference Proceedings
Publisher : Intelligent Systems Technologies and Applications, Springer International Publishing
Source : Intelligent Systems Technologies and Applications, Springer International Publishing, Cham (2018)
ISBN : 9783319683850
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science
Year : 2018
Abstract : The recommendation of products of interest to the user is pivotal for improving a customer's shopping experience. Recommender system has diversified and endeared itself in wide ranging industrial applications from e-commerce to online video sites. As the input data that is supplied to the recommender systems is large, the recommender system is often considered as data intensive application. In this paper, we present improvised MapReduce based data preprocessing and content based recommendation algorithms. Also, Spark based content based recommendation algorithm is developed and compared with Hadoop based content based recommendation algorithm. Our experimental results on Amazon co-purchasing network meta data show that Spark based content based recommendation algorithm is faster than Hadoop based content based recommendation algorithm. Also, graphical user interface is developed to interact with the recommender system.
Cite this Research Publication : S. Saravanan, K.E., K., Balaji, A., and Sajith, A., “Performance Comparison of Apache Spark and Hadoop Based Large Scale Content Based Recommender System”, Intelligent Systems Technologies and Applications. Springer International Publishing, Cham, 2018.