A Deterministic Model for Determining Degree of Friendship Based on Mutual Likings and Recommendations on OTT Platforms

Author:

Khalique Aqeel1ORCID,Rahmani Mohammad Khalid Imam2ORCID,Saquib Mohd1ORCID,Hussain Imran1ORCID,Muzaffar Abdul Wahab2ORCID,Ahad Mohd. Abdul1ORCID,Nafis Md Tabrez1ORCID,Ahmad Mohd Wazih3ORCID

Affiliation:

1. Department of Computer Science & Engineering, Jamia Hamdard, New Delhi, India

2. College of Computing and Informatics, Saudi Electronic University, Riyadh, Saudi Arabia

3. ASTU, Adama, Ethiopia

Abstract

In recent years, the application of various recommendation algorithms on over-the-top (OTT) platforms such as Amazon Prime and Netflix has been explored, but the existing recommendation systems are less effective because either they fail to take an advantage of exploiting the inherent user relationship or they are not capable of precisely defining the user relationship. On such platforms, users generally express their preferences for movies and TV shows and also give ratings to them. For a recommendation system to be effective, it is important to establish an accurate and precise relationship between the users. Hence, there is a scope of research for effective recommendation systems that can define a relationship between users and then use the relationship to enhance the user experiences. In this research article, we have presented a hybrid recommendation system that determines the degree of friendship among the viewers based on mutual liking and recommendations on OTT platforms. The proposed enhanced model is an effective recommendation model for determining the degree of friendship among viewers with improved user experience.

Publisher

Hindawi Limited

Subject

General Mathematics,General Medicine,General Neuroscience,General Computer Science

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