Movie recommender engine using collaborative filtering

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Abstract

The purpose of this paper is to research and form the hybrid algorithm using different collaborative algorithms to achieve the smart clustering to get efficient results. The volume of data which includes both unstructured and structured, and its knowledge has fully grown heavily in recent days. Recommendation system is changing into growingly widespread as they are victimization all over in E-commerce space. Managing large amount of data and information and testing both trained data and tested data to give best recommendation are the main aspects of the project. A massive framework which is used for processing distributed data called Apache Spark is used in the project. As compared to old mapping functions, Spark handles repetitive algorithms, interactive algorithms, and stripped down intervals of time (Swapna in A recommendation engine using Apache Spark, 2015) [1].

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APA

Sadanand, H., Vrushali, D., Rohan, N., Avadhut, M., Rushikesh, V., & Harshada, R. (2018). Movie recommender engine using collaborative filtering. In Smart Innovation, Systems and Technologies (Vol. 78, pp. 599–608). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-10-5547-8_62

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