Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
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.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9262467 | PMC |
http://dx.doi.org/10.1155/2022/9576468 | DOI Listing |
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