AI research paper on knowledge graph embeddings accepted at IEEE ICDM 2026

A research paper titled "ATLAS: Adaptive Attribute-Aware Post-Hoc Alignment of Knowledge Graph Embeddings" has been accepted for presentation at the IEEE International Conference on Data Mining (ICDM) 2026. The conference is scheduled to take place from November 12–15 in Shenyang, China. The paper's authors include Duygu Ekinci, N'Dah Jean Kouagou, Mohamed Ahmed Sherif, and Axel Ngonga. AI

IMPACT This research contributes to the field of knowledge graph embeddings, potentially improving AI systems that rely on structured knowledge.

RANK_REASON The cluster reports on the acceptance of an academic research paper for a conference. [lever_c_demoted from research: ic=1 ai=1.0]

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• ATLAS: Adaptive Attribute-Aware Post-Hoc Alignment of Knowledge Graph Embeddings
• Data Mining
• Duygu Ekinci
• IEEE ICDM 2026
• Knowledge Graphs
• Mohamed Ahmed Sherif
• N'Dah Jean Kouagou
• Shenyang

• paper

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