UvA, TU Delft and Booking.com collaborate on research into better recommendation systems.
ENPNewswire-June 24, 2021--UvA, TU Delft and Booking.com collaborate on research into better recommendation systems
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Release date- 23062021 - In the Mercury Machine Learning Lab, researchers from the University of Amsterdam (UvA) and Delft University of Technology (TU Delft) will be working together with Booking.com on various improved recommendation systems.
The collaboration provides the unique opportunity to test AI techniques in the real world, allowing new machine learning methods to be safely developed for wide application, for example in mobility, energy or healthcare.
Every day, millions of travellers from all over the world make multiple decisions on Booking.com related to their upcoming travel plans. With all of these taps and clicks on property photos and scrolling through search results, Booking.com naturally has a wealth of data insights to help the company make changes on the platform to improve the customer experience. In addition to the responsibility of handling all of this information securely and ethically, how do you analyse all of this data properly and continue to make useful recommendations for customers? Is what works well for a Dutch traveller equally as relevant for a traveller from Japan? And how do you ensure that customers continue to receive interesting travel recommendations that are relevant to them without getting stuck in a filter bubble?
On the road to even better recommendations
One way to understand what constitutes a good recommendation is looking at what previous travellers have chosen and the experiences that their choices yielded. Machine learning techniques are well suited to learning such connections and preferences. However, the problem is that the connections and preferences found in the data are not only informed by the choices of other travellers, but also by the suggestions and selections the system showed them. In the Mercury Machine Learning Lab, researchers from the University of Amsterdam (UvA) and Delft University of Technology will work together with data scientists from Booking.com to develop methods that will ensure that this type of bias is avoided and that the learned connections remain accurate in a new or different context.
From the classroom to real-time e-commerce
Joris Mooij, scientific director of the Mercury Machine Learning Lab at the UvA: 'It's a huge opportunity for us as researchers to have access to a live dataset of...
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