#Meet Concept2Box: Bridging the Gap Between High-Level Concepts and Fine-Grained Entities in Knowledge Graphs – A Dual Geometric Approach

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Meet Concept2Box: Bridging the Gap Between High-Level Concepts and Fine-Grained Entities in Knowledge Graphs A Dual Geometric Approach

📢 Exciting News! Introducing Concept2Box, a Dual Geometric Approach that bridges the gap between high-level concepts and fine-grained entities in knowledge graphs. 🌐🔀 Learn how Concept2Box employs dual geometric representations, using box embeddings for concepts and vector embeddings for entities, enabling the learning of hierarchical structures and complex relationships within knowledge graphs. 📚📊 Discover how this approach addresses the limitations of traditional methods, capturing structural distinctions and hierarchical relationships more effectively. Experimental evaluations on DBpedia and an industrial knowledge graph have shown the remarkable effectiveness of Concept2Box. 💡📈 Grab a coffee and dive deeper into the details here: [Link to Blog Post](https://ift.tt/5uSB73Q) Remember to stay informed about the latest developments and insights from AI Lab Itinai.com by following them on Twitter (@itinaicom). 📣🔑 #knowledgegraphs #datascience #AI #Concept2Box #geometricapproach List of Useful Links: AI Scrum Bot - ask about AI scrum and agile Our Telegram @itinai Twitter -  @itinaicom