In the past, most search queries issued to a search engine were short and simple. A keyword based search engine was able to answer such queries quite well. However, members are now developing the habit of issuing long and complex natural language queries. Answering such queries requires evolution of a search engine to have semantic capability. In this paper we present the design of LinkedIn's new content search engine with semantic capability, and its impact on metrics.
@article{arxiv.2412.20366,
title = {Introducing Semantic Capability in LinkedIn's Content Search Engine},
author = {Xin Yang and Rachel Zheng and Madhumitha Mohan and Sonali Bhadra and Pansul Bhatt and Lingyu and Zhang and Rupesh Gupta},
journal= {arXiv preprint arXiv:2412.20366},
year = {2025}
}