Expedia Partner Solutions is using deep learning models to improve the hotel booking process for partners and – ultimately – the end consumer.
The company is employing a three-stage process with a deployment algorithm sorting properties for its Rapid API to deliver to different partners whether airline, retail store or perhaps corporate travel partner.
Describing it as an “advanced, cutting-edge deep-learning model,” Nuno Castro, chief data scientist for Expedia Partner Solutions (EPS), says:
“We have half a million properties, and we’re signing 15,000 every month, so how do we decide which to give to each partner given that adding them is very complex because we need to match with competitors and other suppliers?
“It’s based on how well each property is going to work for them, for example, a property in central London or at the airport, which should they add to their system?”
The second stage is about real-time sorting of the properties according to who is searching on a partner’s website so that relevant results are presented whether the customer is a corporate traveler or family or other traveler type.
The third stage, which Castro says EPS is launching, is a recommendation API, which kicks in with similar properties that might be a better fit, whilst the traveler is exploring a property they like.
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