Construction and Application of Meituan's Common‑Sense Concept Knowledge Graph

The paper describes Meituan’s common‑sense concept knowledge graph, detailing a multi‑stage construction pipeline—concept, hierarchy, attribute, bridging, and POI/SPU linking—using BERT, XGBoost, and graph neural networks, and demonstrates its deployment in category‑word enrichment, search suggestions, and medical‑beauty tagging, achieving over two million concepts, three million relations, and roughly 90 % accuracy.

Knowledge Graphconcept miningentity linking

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Construction and Application of Meituan's Common‑Sense Concept Knowledge Graph

DataFunTalk

Aug 24, 2020 · Artificial Intelligence

Short Text Understanding in the Medical Health Domain: Business Scenarios and Technical Practices

This presentation details the challenges and solutions for short‑text understanding in medical health, covering DingXiangYuan’s business scenarios, NLP pipeline components, knowledge‑graph construction, concept mining, and their impact on search, recommendation, and tagging systems.

NLPShort Text Understandingconcept mining

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Short Text Understanding in the Medical Health Domain: Business Scenarios and Technical Practices

Alibaba Cloud Developer

Apr 8, 2019 · Artificial Intelligence

How Alibaba Builds a Massive E‑Commerce Concept Graph to Power Search & Recommendation

This article explains how Alibaba’s Search & Recommendation team constructs a large‑scale e‑commerce concept graph—defining e‑commerce concepts, mining them from queries and titles, building an ontology, linking concepts to entities, and applying the graph to improve personalized search and recommendation.

Knowledge GraphOntologySearch

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