scenario_recommendationsystem-todo.md

Scenario_RecommendationSystem-[TODO]

• Recommendation system
  • Use cases
  • Components
  • Overview
    • Cold start
    • Offline processing
    • Online processing
  • Design
    • Version 1
    • Version 2
    • Version 3

Recommendation system

Use cases

• Long tail
• Utilize the traffic
• Same or close categories of products
  • Collaborative filtering
    • e.g. The number of people viewing A 10, the number of people viewing B 20. The number of people viewing A and B is 5. Then the correlation coefficient between A and B is "A intersect B" / "A union B"

Components

• Regression
• Sort

Overview

Cold start

• Recommend something popular
  1. Based on the content / based on the user behavior
  2. Compute the correlation coefficient
  3. Sort

Offline processing

Online processing

Design

Version 1

• No user customization
• Factors
  • Number of pictures
  • The length of online
• Fixed weights
• Making sure that not all results come from a single saler
• No support for online user testing

Version 2

• Overtime users have accumulated their behavior
• Record users' behavior into Hadoop cluster

Version 3