In everyday life recommendation system plays an important role and collaborative filtering (CF) is used widely in many e-commerce applicationsfor online product recommendation. A recommender system is mainly used for better predictions as better decision making by using preferences during searching, shopping etc. The preferences of other users, user`s past preferences and big data is the driving force behind Recommendation systems. In this paper, we present collaborative filter types and their main challenges. Using the open source library Apache Mahout, we implemented collaborative filter using single-criteria to recommend items to particular users. Also, we showed the flow of Apache Mahout command�s execution to process the huge data using LogLikelihood similarity algorithm in big data scenario.

Recommendation system; Collaborative filtering; Apache Mahout; Big data; Hive

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