Query Brand Entity Linking in E-Commerce Search
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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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 17 of its 40 references that are in the map. First posted on arXiv 3 Feb 2025.
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References · 17
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- 2019Distant Learning for Entity Linking with Automatic Noise Detectioncited by 11
5 more
- 2018Mixing Context Granularities for Improved Entity Linking on Question Answering Data across Entity Categoriescited by 9
- 2024Exploring Query Understanding for Amazon Product Searchcited by 6
- 2017Entity Linking for Queries by Searching Wikipedia Sentencescited by 5
- 2020Distant-Supervised Slot-Filling for E-Commerce Queriescited by 2
- 2024REXEL: An End-to-end Model for Document-Level Relation Extraction and Entity Linkingcited by 2
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