图 书 馆
在Airbnb使用嵌入式搜索排名实现实时个性化Real‑time Personalization using Embeddings for Search Ranking at Airbnb |
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| 课程网址: | http://videolectures.net/kdd2018_grbovic_search_ranking_at_airbnb... |
| 主讲教师: | Mihajlo Grbovic |
| 开课单位: | 天普大学数据分析和生物医学信息学中心 |
| 开课时间: | 2018-11-23 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Search Ranking and Recommendations are fundamental problems of crucial interest to major Internet companies, including web search engines, content publishing websites and marketplaces. However, despite sharing some common characteristics a one-size-fits-all solution does not exist in this space. Given a large difference in content that needs to be ranked, personalized and recommended, each marketplace has a somewhat unique challenge. Correspondingly, at Airbnb, a short-term rental marketplace, search and recommendation problems are quite unique, being a two-sided marketplace in which one needs to optimize for host and guest preferences, in a world where a user rarely consumes the same item twice and one listing can accept only one guest for a certain set of dates. In this paper we describe Listing and User Embedding techniques we developed and deployed for purposes of Real-time Personalization in Search Ranking and Similar Listing Recommendations, two channels that drive 99% of conversions. The embedding models were specifically tailored for Airbnb marketplace, and are able to capture guest’s short-term and long-term interests, delivering effective home listing recommendations. We conducted rigorous offline testing of the embedding models, followed by successful online tests before fully deploying them into production. |
| 关 键 词: | Airbnb使用嵌入式搜索; 搜索排名实现实时个性化; 搜索排名和推荐 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-03-27：cyh |
| 最后编审: | 2023-03-27：cyh |
| 阅读次数: | 33 |