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A Deterministic Model for Determining Degree of Friendship Based on Mutual Likings and Recommendations on OTT Platforms
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 relations...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9262467/ https://www.ncbi.nlm.nih.gov/pubmed/35814586 http://dx.doi.org/10.1155/2022/9576468 |
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author | Khalique, Aqeel Rahmani, Mohammad Khalid Imam Saquib, Mohd Hussain, Imran Muzaffar, Abdul Wahab Ahad, Mohd. Abdul Nafis, Md Tabrez Ahmad, Mohd Wazih |
author_facet | Khalique, Aqeel Rahmani, Mohammad Khalid Imam Saquib, Mohd Hussain, Imran Muzaffar, Abdul Wahab Ahad, Mohd. Abdul Nafis, Md Tabrez Ahmad, Mohd Wazih |
author_sort | Khalique, Aqeel |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9262467 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-92624672022-07-08 A Deterministic Model for Determining Degree of Friendship Based on Mutual Likings and Recommendations on OTT Platforms Khalique, Aqeel Rahmani, Mohammad Khalid Imam Saquib, Mohd Hussain, Imran Muzaffar, Abdul Wahab Ahad, Mohd. Abdul Nafis, Md Tabrez Ahmad, Mohd Wazih Comput Intell Neurosci Research Article 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. Hindawi 2022-06-30 /pmc/articles/PMC9262467/ /pubmed/35814586 http://dx.doi.org/10.1155/2022/9576468 Text en Copyright © 2022 Aqeel Khalique et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Khalique, Aqeel Rahmani, Mohammad Khalid Imam Saquib, Mohd Hussain, Imran Muzaffar, Abdul Wahab Ahad, Mohd. Abdul Nafis, Md Tabrez Ahmad, Mohd Wazih A Deterministic Model for Determining Degree of Friendship Based on Mutual Likings and Recommendations on OTT Platforms |
title | A Deterministic Model for Determining Degree of Friendship Based on Mutual Likings and Recommendations on OTT Platforms |
title_full | A Deterministic Model for Determining Degree of Friendship Based on Mutual Likings and Recommendations on OTT Platforms |
title_fullStr | A Deterministic Model for Determining Degree of Friendship Based on Mutual Likings and Recommendations on OTT Platforms |
title_full_unstemmed | A Deterministic Model for Determining Degree of Friendship Based on Mutual Likings and Recommendations on OTT Platforms |
title_short | A Deterministic Model for Determining Degree of Friendship Based on Mutual Likings and Recommendations on OTT Platforms |
title_sort | deterministic model for determining degree of friendship based on mutual likings and recommendations on ott platforms |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9262467/ https://www.ncbi.nlm.nih.gov/pubmed/35814586 http://dx.doi.org/10.1155/2022/9576468 |
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