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  • Recommendation system
  • Use cases
  • Components
  • Overview
  • Design

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  1. TODO

RecommendationSystem-[TODO]

PreviousinterviewRecordNextSessionServer-[TODO]

Last updated 3 years ago

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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

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