Manuscript Number : CSEIT19511
Movie Recommended System by Using Collaborative Filtering
Authors(3) :-Bheema Shireesha, Navuluri Madhavilatha, Chunduru Anilkumar Recommendation system helps people in decision making an item/person. Recommender systems are now pervasive and seek to make profit out of customers or successfully meet their needs. Companies like Amazon use their huge amounts of data to give recommendations for users. Based on similarities among items, systems can give predictions for a new item’s rating. Recommender systems use the user, item, and ratings information to predict how other users will like a particular item. In this project, we attempt to under- stand the different kinds of recommendation systems and compare their performance on the Movie Lens dataset. Due to large size of data, recommendation system suffers from scalability problem. Hadoop is one of the solutions for this problem.
Bheema Shireesha Hadoop, Collaborative filtering, Machine Learning, HDFS, RSSI Publication Details Published in : Volume 5 | Issue 1 | January-February 2019 Article Preview
Assistant Professor, Department of Computer Science and Engineering, Dr. APJ Abdul Kalam IIIT Ongole, Andhra Pradesh, India
Navuluri Madhavilatha
Guest Faculty, Department of Computer Science and Engineering, Dr. APJ Abdul Kalam IIIT Ongole, Andhra Pradesh, India
Chunduru Anilkumar
Assistant Professor, Department of Computer Science and Engineering, Dr. APJ Abdul Kalam IIIT Ongole, Andhra Pradesh, India
Date of Publication : 2019-01-30
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 09-15
Manuscript Number : CSEIT19511
Publisher : Technoscience Academy
Journal URL : https://res.ijsrcseit.com/CSEIT19511
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