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TransKGQA: Enhanced Knowledge Graph Question Answering With Sentence Transformers

You Li Chong, Chin Poo Lee, Shahrin Zen Muhd-Yassin, Kian Ming Lim et al. • IEEE Access (2024)

Knowledge Graph Question Answering (KGQA) plays a crucial role in extracting valuable insights from interconnected information. Existing methods, while commendable, face challenges such as contextual ambiguity and limited adaptability to di...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3405583

Semantic Alignment in Disciplinary Tutoring System: Leveraging Sentence Transformer Technology

Rosana Abdoune, Lydia Lazib, Farida Dahmani-Bouarab, Nada Mimouni • Inteligencia Artificial (2024)

In this work, we present a disciplinary e-tutoring system that integrates ONTO-TDM, an ontology designed for teaching domain modeling, with advanced transformer technology. Our primary objective is to enhance semantic similarity tasks withi...

DOAJ Open Access (DOAJ)