The Netflix Recommender System

Added on - 21 Apr 2020

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Running head:THE NETFLIX RECOMMENDER SYSTEMThe Netflix Recommender SystemName of the student:Name of the university:Author Note
1THE NETFLIX RECOMMENDER SYSTEM1. AbstractThe recommendation systems change the approaches by which the inanimate websites are found tobe communicating with the users. The survey paper is created to demonstrate the two academicjournals keeping the case of Netflix Recommendation Algorithm in mind.2. Keywords:Netflix Recommendation Algorithm, recommender system, algorithm, culture.
2THE NETFLIX RECOMMENDER SYSTEMTable of Contents3. Introduction:......................................................................................................................................34. Related work, description of recommendation algorithm:................................................................34.1. The Netflix Recommender System: Algorithms, Business Value and Innovation:...................34.2. Recommended for you: The Netflix Prize and the production of algorithmic culture:..............55. Conclusion:........................................................................................................................................86. References:........................................................................................................................................9
3THE NETFLIX RECOMMENDER SYSTEM3. Introduction:The recommendation systems have been changing the methods in which the inanimatewebsites have been communicating with the users. They identify the recommendationsautonomously for every user on the previous searches and purchases along with the behavior ofother users.The rating prediction algorithm researched in the Netflix Prize is referred to as the “NetflixRecommendation Algorithm”. The following survey paper is developed to analyze the two academicjournals referring to the case of Netflix Recommendation Algorithm.4. Related work, description of recommendation algorithm:4.1. The Netflix Recommender System: Algorithms, Business Value and Innovation:The above article has analyzed various algorithms making up the Netflix recommendersystem along with the business purposes. It has also included the roles of search and the relevantalgorithms turning to be recommendation problems also. The motivations and the review of theapproach are also explained for improving the recommendation algorithm [1]. It has combined theA/B testing concentrating on the developing member retention and the mid-term engagement.Further analysis is done on the offline experimentation through the engagement data of the historicalmembers. Lastly, the issues to design and interpret the A/B tests are discussed long with the presentsectors of the focused innovation. This has been including the recommender system aware of thelanguage and areas.The Netflix has been lying in the mid of Internet and storytelling. The enterprise has beenpermitting the members to steam videos in their various collections of TV shows and movies at anytime over the broad range of the devices connected to the Internet. The Netflix Recommender
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