How Airbnb Tells You Will Enjoy Sunset Sailing in Barcelona? Recommendation in a Two-Sided Travel Marketplace

Abstract

A two-sided travel marketplace is an E-Commerce platform where users can both host tours or activities and book them as a guest. When a new guest visits the platform, given tens of thousands of available listings, a natural question is that what kind of activities or trips are the best fit. In order to answer the question, a recommender system needs to both understand characteristics of its inventories, and to know the preferences of each individual guest. In this work, we present our efforts on building a recommender system for Airbnb Experiences, a two-sided online marketplace for tours and activities. Traditional recommender systems rely on abundant user-listing interactions. Airbnb Experiences is an emerging business where many listings and guests are new to the platform. Instead of passively waiting for data to accumulate, we propose novel approaches to identify key features of a listing and estimate guest preference with limited data availability.