A Research on Collaborative Filtering Based Movie Recommendations: From Neighborhood to Deep Learning Based System
Dayal Kumar Behera1, Madhabananda Das2, SubhraSwetanisha3
1Dayal Kumar Behera, Department of CSE, KIIT University, Bhubaneswar, India.
2Madhabananda Das, Department of CSE, KIIT University, Bhubaneswar, India.
3SubhraSwetanisha, Department of CSE, Trident Academy of Technology, Bhubaneswar, India. 

Manuscript received on November 11, 2019. | Revised Manuscript received on November 20 2019. | Manuscript published on 30 November, 2019. | PP: 10809-10814 | Volume-8 Issue-4, November 2019. | Retrieval Number: D4362118419/2019©BEIESP | DOI: 10.35940/ijrte.D4362.118419

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Recommender System or Recommendation Engine gaining popularity as it can tackle information overload problem. Initially it was considered as a domain of Information Retrieval system and was limited to few applications. With the advancement of different state-of-the-art modeling approaches recommender system can be applicable to many application domains. Movie Recommender System (MRS) is widely explored domain and used by many streaming service providers like Netflix, Amazon Prime, YouTube and many more. This system makes use of users’ data to explore and recommends personally as per their taste. In this paper a detailed study on recently published article related to movie recommendation is carried out. Popular techniques for MRS are commonlycategorized into collaborative filtering, content-based and hybridmethod. Neighborhood-based, latent factor based, neural network based and deep learning based techniques have been continuously evolved with application to MRS. Recently proposed models have been reviewed and it is found that hybrid method performs better as compared to individual model.
Keywords: Movie Recommender System, Latent Factor Model, Deep Learning Model, Collaborative filtering.
Scope of the Article: Deep Learning.