Trustworthy AI to build fair webshops

Trading platforms like Bol.com or Amazon, always show a customer recommendations for follow-up purchases based on the last purchase the customer made. Determine if these existing algorithms can be improved.

Required interest(s)

  • Data
  • Artificial Intelligence

What do you get

  • A challenging assignment within a practical environment
  • € 1000 compensation, € 500 + lease car or € 600 + living space
  • Professional guidance
  • Courses aimed at your graduation period
  • Support from our academic Research center at your disposal
  • Two vacation days per month

What you will do

  • 65% Research
  • 10% Analyze, design, realize
  • 25% Documentation

The AI behind these recommendation engines, is often biased to promote those sales partners that have the biggest sales on the platform, where for a particular customer a smaller partner might be more relevant. these recommendation engines frequently suggest products that are not relevant to a customer at all, for example when the product has already been bought. This especially occurs when the sales platform is visited by multiple users on one account. For example when a couple uses one account.

Perform a literature research to determine if research has been done to the cause of these bias errors in recommendation engines. Investigate what causes the problems described by investigating existing recommendation algorithms. Determine if one of these existing algorithms can be improved, or whether a new implementation is necessary. Prove the correctness of your research by implementing a recommendation engine in a mockup webshop that provides a fair recommendation where all sales partners get an equal chance and where the customer can provide feedback to provided recommendations which is used by the engine to improve future recommendations.

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