8 papers · 1 filter
High Precision Audience Expansion via Extreme Classification in a Two-Sided Marketplace
Dillon Davis, Huiji Gao, Thomas Legrand +8
Airbnb search must balance a worldwide, highly varied supply of homes with guests whose location, amenity, style, and price expectations differ widely. Meeting those expectations h…
Applying Embedding-Based Retrieval to Airbnb Search
Mustafa Abdool, Soumyadip Banerjee, Moutupsi Paul +10
The goal of Airbnb search is to match guests with the ideal accommodation that fits their travel needs. This is a challenging problem, as popular search locations can have around a…
Learning to Comparison-Shop
Jie Tang, Daochen Zha, Xin Liu +4
In online marketplaces like Airbnb, users frequently engage in comparison shopping before making purchase decisions. Despite the prevalence of this behavior, a significant disconne…
Harnessing the Power of Interleaving and Counterfactual Evaluation for Airbnb Search Ranking
Qing Zhang, Alex Deng, Michelle Du +3
Evaluation plays a crucial role in the development of ranking algorithms on search and recommender systems. It enables online platforms to create user-friendly features that drive…
Beyond Pairwise Learning-To-Rank At Airbnb
Malay Haldar, Daochen Zha, Huiji Gao +2
There are three fundamental asks from a ranking algorithm: it should scale to handle a large number of items, sort items accurately by their utility, and impose a total order on th…
Transforming Location Retrieval at Airbnb: A Journey from Heuristics to Reinforcement Learning
Dillon Davis, Huiji Gao, Thomas Legrand +6
The Airbnb search system grapples with many unique challenges as it continues to evolve. We oversee a marketplace that is nuanced by geography, diversity of homes, and guests with…