Collaborative filtering-based recommendation system for big data Online publication date: Wed, 11-Mar-2020
by Jian Shen; Tianqi Zhou; Lina Chen
International Journal of Computational Science and Engineering (IJCSE), Vol. 21, No. 2, 2020
Abstract: Collaborative filtering algorithm is widely used in the recommendation system of e-commerce website, which is based on the analysis of a large number of users' historical behaviour data, so as to explore the users' interest and recommend the appropriate products to users. In this paper, we focus on how to design a reliable and highly accurate algorithm for movie recommendation. It is worth noting that the algorithm is not limited to film recommendation, but can be applied in many other areas of e-commerce. In this paper, we use Java language to implement a movie recommendation system in Ubuntu system. Benefiting from the MapReduce framework and the recommendation algorithm based on items, the system can handle large datasets. The experimental results show that the system can achieve high efficiency and reliability in large datasets.
Online publication date: Wed, 11-Mar-2020
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