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Applying Deep Learning To Airbnb Search

Applying Deep Learning To Airbnb Search

陈重丶
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The application to search ranking is one of the biggest machine learning success stories at Airbnb. Much of the initial gains were
driven by a gradient boosted decision tree model. !e gains, however, plateaued over time. !is paper discusses the work done in
applying neural networks in an a”empt to break out of that plateau. We present our perspective not with the intention of pushing the
frontier of new modeling techniques. Instead, ours is a story of the elements we found useful in applying neural networks to a real life product. Deep learning was steep learning for us. To other teams embarking on similar journeys, we hope an account of our struggles and triumphs will provide some useful pointers.

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