# Query Brand Entity Linking in E-Commerce Search

arXiv: https://arxiv.org/abs/2502.01555 · HTML: https://mlsanity.com/paper/2502.01555/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 17 of its 40 references that are in the map.
- First posted on arXiv 3 Feb 2025.

## Builds on (most cited first, 17 of 17)

- [DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter](https://mlsanity.com/paper/1910.01108/) (2019)
- [Knowledge Enhanced Contextual Word Representations](https://mlsanity.com/paper/1909.04164/) (2019)
- [Transformer Memory as a Differentiable Search Index](https://mlsanity.com/paper/2202.06991/) (2022)
- [Zero-Shot Entity Linking by Reading Entity Descriptions](https://mlsanity.com/paper/1906.07348/) (2019)
- [End-to-End Neural Entity Linking](https://mlsanity.com/paper/1808.07699/) (2018)
- [Efficient One-Pass End-to-End Entity Linking for Questions](https://mlsanity.com/paper/2010.02413/) (2020)
- [PECOS: Prediction for Enormous and Correlated Output Spaces](https://mlsanity.com/paper/2010.05878/) (2020)
- [Extreme Multi-label Learning for Semantic Matching in Product Search](https://mlsanity.com/paper/2106.12657/) (2021)
- [Extreme Zero-Shot Learning for Extreme Text Classification](https://mlsanity.com/paper/2112.08652/) (2021)
- [Leveraging Deep Neural Networks and Knowledge Graphs for Entity Disambiguation](https://mlsanity.com/paper/1504.07678/) (2015)
- [QUEACO: Borrowing Treasures from Weakly-labeled Behavior Data for Query Attribute Value Extraction](https://mlsanity.com/paper/2108.08468/) (2021)
- [Distant Learning for Entity Linking with Automatic Noise Detection](https://mlsanity.com/paper/1905.07189/) (2019)
- [Mixing Context Granularities for Improved Entity Linking on Question Answering Data across Entity Categories](https://mlsanity.com/paper/1804.08460/) (2018)
- [Exploring Query Understanding for Amazon Product Search](https://mlsanity.com/paper/2408.02215/) (2024)
- [Entity Linking for Queries by Searching Wikipedia Sentences](https://mlsanity.com/paper/1704.02788/) (2017)
- [Distant-Supervised Slot-Filling for E-Commerce Queries](https://mlsanity.com/paper/2012.08134/) (2020)
- [REXEL: An End-to-end Model for Document-Level Relation Extraction and Entity Linking](https://mlsanity.com/paper/2404.12788/) (2024)

## Abstract (arXiv)

Associating user search queries with the correct brand entity is critical for e-commerce product retrieval, yet remains challenging due to the brevity of queries (three to four words on average), their lack of grammatical structure, and a catalog of hundreds of thousands of distinct brands. We formulate this as a brand entity linking task and develop two complementary solutions deployed at scale: (1) a cascaded pipeline that first detects brand mentions via sequence labeling and then disambiguates against a brand knowledge base, and (2) a single-stage approach that frames linking as extreme multiclass classification, directly mapping queries to brand identifiers. Through extensive multilingual evaluation (11 languages) and a controlled online experiment, we demonstrate that the proposed methods substantially improve brand recall while maintaining high precision, leading to measurable gains in customer engagement.