دوره 18، شماره 1 - ( مجله کنترل، جلد 18، شماره 1، بهار 1403 )
جلد 18 شماره 1,1403 صفحات 43-13 |
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Tohidi N, Dadkhah C, Gelbukh A. Abstract Meaning Representation: A State-of-the-Art Review. JoC 2024; 18 (1) :13-43
URL: http://joc.kntu.ac.ir/article-1-1044-fa.html
URL: http://joc.kntu.ac.ir/article-1-1044-fa.html
توحیدی نسیم، دادخواه چیترا، Gelbukh Alexander. بازنمایی معنای انتزاعی: مروری بر کارهای اخیر. مجله کنترل. 1403; 18 (1) :13-43
1- گروه مهندسی هوش مصنوعی، دانشکده مهندسی کامپیوتر، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران، ایران
2- موسسه ملی پلی تکنیک
2- موسسه ملی پلی تکنیک
چکیده: (183 مشاهده)
کاربرد بازنمایی معنای انتزاعی (AMR) به طور گسترده‌ای به عنوان شکل اصلی معناشناسی ساختاریافته در حال افزایش است و به عنوان نقطه عطفی برای تحقیقات پردازش زبان طبیعی (NLP) در نظر گرفته می‌شود. AMRها، در واقع، گراف‌های ریشه‌دار و برچسب‌گذاری شده‌ای هستند که معنای یک متن را در سطح جمله بازنمایی می‌کنند و این کار را به صورت مستقل از ساختار نحوی جمله انجام می‌دهند. گره‌های گراف مفاهیم را در معنای جمله نشان می‌دهند و برچسب‌های یال‌ها معادل روابط بین این مفاهیم هستند. در این مقاله، مروری بر رویکردهای موجود در تولید متن از AMR و تجزیه متن ورودی برای تولید AMR با مطالعه تحقیقات مختلف از سال 2013 تا 2022 ارائه نموده‌ایم. علاوه بر این، توضیح می‌دهیم که چگونه محققان تاکنون از AMR برای کاربردهای رایج NLP استفاده کرده‌اند. پس از آن، مجموعه داده‌ها و معیارهای ارزیابی مرتبط موجود در این زمینه را شرح می‌دهیم. در نهایت، برخی از ویژگی‌ها و چالش‌های اساسی AMR را مورد بحث قرار خواهیم داد.
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