Query Brand Entity Linking in E-Commerce Search
cs.IR, cs.AI, cs.LG
Submitted: 2025-02-03
Updated: 2026-09-09
Comments: Accepted by CIKM
Journal ref: CIKM 2026
DOI: 10.1145/3799682.3840092 10.1145/3799682.3840092
License: http://creativecommons.org/licenses/by-nc-nd/4.0/
The gist: 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),
Terminology
Abstract
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.
Sources
- Leveraging Deep Neural Networks and Knowledge Graphs for Entity Disambiguation
- End-to-End Neural Entity Linking
- Knowledge Enhanced Contextual Word Representations
- Neural Entity Linking: A Survey of Models Based on Deep Learning
- Mixing Context Granularities for Improved Entity Linking on Question Answering Data across Entity Categories
- Transformer Memory as a Differentiable Search Index
- Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models
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