基于嵌入的Airbnb搜索检索

Our journey in applying embedding-based retrieval techniques to build an accurate and scalable candidate retrieval system for Airbnb Homes search

我们在应用基于嵌入的检索技术以构建一个准确且可扩展的Airbnb Homes搜索候选检索系统的旅程

Authors: Mustafa (Moose) Abdool, Soumyadip Banerjee, Karen Ouyang, Do-Kyum Kim, Moutupsi Paul, Xiaowei Liu, Bin Xu, Tracy Yu, Hui Gao, Yangbo Zhu, Huiji Gao, Liwei He, Sanjeev Katariya

作者： Mustafa (Moose) Abdool， Soumyadip Banerjee， Karen Ouyang， Do-Kyum Kim， Moutupsi Paul， Xiaowei Liu， Bin Xu， Tracy Yu， Hui Gao， Yangbo Zhu， Huiji Gao， Liwei He， Sanjeev Katariya

Introduction

介绍

Search plays a crucial role in helping Airbnb guests find the perfect stay. The goal of Airbnb Search is to surface the most relevant listings for each user’s query — but with millions of available homes, that’s no easy task. It’s especially difficult when searches include large geographic areas (like California or France) or high-demand destinations (like Paris or London). Recent innovations — such as flexible date search, which allows guests to explore stays without fixed check-in and check-out dates — have added yet another layer of complexity to ranking and finding the right results.

搜索在帮助Airbnb客人找到完美住宿方面发挥着至关重要的作用。Airbnb搜索的目标是为每个用户的查询呈现最相关的房源——但在数百万个可用房源中，这并非易事。当搜索包括大地理区域（如加利福尼亚或法国）或高需求目的地（如巴黎或伦敦）时，尤其困难。最近的创新——例如灵活日期搜索，允许客人探索没有固定入住和退房日期的住宿——为排名和找到正确结果增加了另一层复杂性。

To tackle these challenges, we need a system that can retrieve relevant homes while also being scalable enough (in terms of latency and compute) to handle queries with a large candidate count. In this blog post, we share our journey in building Airbnb’s first-ever Embedding-Based Retrieval (EBR) search system. The goal of this system is to narrow down the initial set of eligible homes into a smaller pool, which can then be scored by more compute-intensive machine learning models later in the search ranking process.

为了解决这些挑战，我们需要一个能够检索相关房源的系统，同时在延迟和计算方面具有足够的可扩展性，以处理候选数量较大的查询。在这篇博客文章中，我们分享了构建 Airbnb 首个基于嵌入的检索（EBR）搜索系统的历程。该系统的目标是将初始的合格房源集缩小到一个较小的池中，然后可以在搜索排名过程中由更计算密集的机器学习模型进行评分。

Figure 1:...