System Design
Recommendation System

Recommendation System

Design a recommendation system that recommends relevant items to users based on their preferences and past behavior. The system should be able to handle a large number of users and a diverse range of items.

Example:

Suppose we need to design a recommendation system for an e-commerce website that sells various products like books, electronics, and clothing. The recommendation system should be able to suggest items that a user is likely to be interested in based on their browsing and purchase history.

Functional Requirements:

  1. Users should be able to view recommended items on the website or app.
  2. The system should be able to recommend items based on a user's past behavior, such as browsing history and purchase history.
  3. Users should be able to provide feedback on recommended items, such as rating or liking them.
  4. The system should be able to incorporate user feedback to improve future recommendations.
  5. The system should be able to recommend items that are relevant and useful to the user.
  6. The system should be able to recommend items across a range of categories, such as books, electronics, and clothing.

Non-functional Requirements:

  1. The system should be able to handle a large number of users and items.
  2. The system should be able to provide recommendations in real-time with low latency.
  3. The system should be able to scale horizontally to handle larger volumes of users and items.
  4. The system should be able to maintain user privacy and protect user data.
  5. The system should be able to handle diverse data types and sources, such as structured and unstructured data.

Assumptions:

  1. The system assumes that users are providing accurate and complete information about their preferences and behavior.
  2. The system assumes that users are not providing deliberately false information to manipulate the recommendations.
  3. The system assumes that users are not trying to exploit the system for personal gain.

Estimated Usage:

  1. The system should be able to handle at least 10 million daily active users.
  2. The system should be able to recommend items across a range of categories, such as books, electronics, and clothing.
  3. The system should be able to handle at least 100,000 requests per second.