Development of a recommendation system for personalized movie streaming
Table Of Contents
<p>1. Introduction<br> - Background and significance of personalized recommendation systems<br> - Objectives and scope of the project<br>2. Literature Review<br> - Overview of recommendation system algorithms<br> - Review of personalized content recommendation in streaming services<br>3. Data Collection and Preprocessing<br> - Collection of user interaction data and movie metadata<br> - Data cleaning and feature extraction<br>4. Recommendation Model Development<br> - Selection of recommendation algorithms<br> - Model training and evaluation<br>5. User Interface Integration<br> - Design and implementation of the recommendation system interface<br> - Integration with movie streaming platform<br></p>
Thesis Abstract
<p> The project focuses on the development of a recommendation system for personalized movie streaming. The system will utilize machine learning algorithms to analyze user preferences and viewing history, and provide personalized movie recommendations to users. The project aims to enhance user satisfaction and engagement by delivering relevant and tailored movie suggestions, thereby improving the overall streaming experience. <br></p>Thesis Overview
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