In this work, we address the brand entity linking problem for e-commerce search queries. The entity linking task is done by either i)a two-stage process consisting of entity mention detection followed by entity disambiguation or ii) an end-to-end linking approaches that directly fetch the target entity given the input text. The task presents unique challenges: queries are extremely short (averaging 2.4 words), lack natural language structure, and must handle a massive space of unique brands. We present a two-stage approach combining named-entity recognition with matching, and a novel end-to-end solution using extreme multi-class classification. We validate our solutions by both offline benchmarks and the impact of online A/B test.
View on arXiv@article{liu2025_2502.01555,
title={ Query Brand Entity Linking in E-Commerce Search },
author={ Dong Liu and Sreyashi Nag },
journal={arXiv preprint arXiv:2502.01555},
year={ 2025 }
}