A Study on Abstract Meaning Representation Applications
محل انتشار: اولین کنفرانس هوش مصنوعی و پردازش هوشمند
سال انتشار: 1401
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 278
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شناسه ملی سند علمی:
AISC01_055
تاریخ نمایه سازی: 16 آبان 1401
چکیده مقاله:
Abstract Meaning Representation (AMR) is a representation model in which AMRs arerooted and labeled graphs that capture semantics on sentence-level and abstract away fromMorpho-Syntactic properties. The graph’s nodes represent meaning concepts, and the edge labelsshow relations between them. AMR application in Natural Language Processing tasks is widelyincreasing as a principal form of structured sentence semantics, and it is considered as a turningpoint for NLP research. In this paper, we studied the recent works on AMR applications in variousNLP tasks, which mostly worked on English language. Moreover, we compare them and discusssome basic features of them.
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نویسندگان
Nasim Tohidi
K. N. Toosi University of Technology, Artificial Intelligence Department, Faculty of Computer Engineering Tehran,Iran
Chitra Dadkhah
K. N. Toosi University of Technology, Artificial Intelligence Department, Faculty of Computer Engineering Tehran,Iran