Job Type Extraction for Service Businesses

Cheng Li, Yaping Qi, Hayk Zakaryan,Mingyang Zhang,Michael Bendersky, Yonghua Wu,Marc Najork

COMPANION OF THE WORLD WIDE WEB CONFERENCE, WWW 2023(2023)

引用 0|浏览62
暂无评分
摘要
Google My Business (GMB) is a platform that hosts business profiles, which will be displayed when a user issues a relevant query on Google Search or Google Maps. GMB businesses provide a wide variety of services, from home cleaning and repair, to legal consultation. However, the exact details of the service provided (a.k.a. job types), are often missing in business profiles. This places the burden of finding these details on the users. To alleviate this burden, we built a pipeline to automatically extract the job types from business websites. We share the various challenges we faced while developing this pipeline, and how we effectively addressed these challenges by (1) utilizing structured content to tackle the cold start problem for dataset collection; (2) exploiting context information to improve model performance without hurting scalability; and (3) formulating the extraction problem as a retrieval task to improve both generalizability, efficiency, and coverage. The pipeline has been deployed for over a year and is scalable enough to be periodically refreshed. The extracted job types are serving users of Google Search and Google Maps, with significant improvements in both precision and coverage.
更多
查看译文
关键词
job type extraction,service
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要