AEAirbnb Engineeringهوش مصنوعیپرو

CASTLE: training natural language search before the first real query

How we addressed the cold start problem for Airbnb’s natural language search by jointly generating synthetic training data — queries and relevance labels — from de identified booking and search signals. By : Wendy Ran Wei , Hao Li , Weiwei Guo , Xiaowei Liu , Xueyin Chen , Chun How Tan , Malay Haldar , Soumyadip…

Wendy Ran Wei ۷ دقیقه مطالعهمتن اصلی

How we addressed the cold-start problem for Airbnb’s natural language search by jointly generating synthetic training data — queries and relevance labels — from de-identified booking and search signals.

View across the lake in St. James’s Park, London, framed by golden autumn willow trees, with the ornate towers and domes of Horse Guards building visible in the background and swans and waterfowl swimming on the water with a fountain spraying in the center.

By: Wendy Ran Wei, Hao Li, Weiwei Guo, Xiaowei Liu, Xueyin Chen, Chun How Tan, Malay Haldar, Soumyadip Banerjee, Kedar Bellare, Huiji Gao, Sanjeev Katariya, and Stephanie Moyerman

Introduction

خواندن Airbnb Engineering با پرو

این منبع جزو کتابخانه پرو است. همه منابع ویژه، ترجمه هوشمند و فیدهای شخصی را باز کنید.

باز کردن با پرواشتراک پرو دارم
#LLM#AI#Machine Learning#Data#technology
AE

منتشرشده در

Airbnb Engineering

خواندن در منبع

ادامه مطالعه