Reverse-engineering cloud-based personalized movie recommendation systems for streaming services Background: Streaming services have become popular for the convenience and comfort they offer.
These services utilize proprietary cloud-based recommendation systems that suggest personalized movie recommendations to users based on their viewing history and preferences. By harnessing the power of cloud computing and collaborative filtering algorithms, this technology allows users to discover new movies they might enjoy, enhancing their movie-watching experience.
Task: This task aims to research and discuss the logical architecture and framework of an online cloud-based personalized movie recommendation system that might be used by a streaming service.
You are free to select a real-world streaming service or utilize a fictional one as your case study. Note that most cloud-based personalized movie recommendation systems used by real-world streaming services are proprietary and are not open-source. Therefore, research, analysis, logical thinking, and approximation are critical for this task.
Your deliverable is a detailed project report documenting the problem statement, current state of the industry, review of related technologies, comparative analysis, recommendations, and conclusions: — Introduce and discuss the topic; provide a narrative of the selected streaming service. — Present and elaborate the theoretical cloud-based personalized movie recommendation system used by your selected streaming service; Justify your assumptions and arguments; Support your discussion with relevant references and use-case. —
Discussion of advantages and disadvantages of the presented system. — Summarize results and provide a strong conclusion. Written as a project report
