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Register a new userBiomedical Concept Normalization by Leveraging Hypernyms
تطبيع المفهوم الطبي الطبيعي من خلال الاستفادة من الارتفاع
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يستخدم تطبيع المفهوم الطبي الحيوي (BCN) على نطاق واسع في معالجة النص الطبية الحيوية كوحدة أساسية.بسبب العديد من المتغيرات السطحية للمفاهيم الطبية الحيوية، لا يزال BCN صعبا وغير مستمر.في هذه الورقة، نمستحم فرطيات المفهوم الطبية الحيوية لتسهيل BCN.نقترح Norkizer مفهوم الطبية الطبية الحيوية مع فرط النعاطات (BCNH)، وهو إطار جديد يتبنى تدريبات قائمة في القائمة للاستفادة من كل من الارتباطات والنظارات المرادفات، وتوظف أيضا قيود المعايير على تمثيل أزواج كيان Hypernym-Hypernym-hyponymy.تظهر النتائج التجريبية أن BCNH تتفوق على نموذج الحالة السابقة في مجموعة بيانات NCBI.
Biomedical Concept Normalization (BCN) is widely used in biomedical text processing as a fundamental module. Owing to numerous surface variants of biomedical concepts, BCN still remains challenging and unsolved. In this paper, we exploit biomedical concept hypernyms to facilitate BCN. We propose Biomedical Concept Normalizer with Hypernyms (BCNH), a novel framework that adopts list-wise training to make use of both hypernyms and synonyms, and also employs norm constraint on the representation of hypernym-hyponym entity pairs. The experimental results show that BCNH outperforms the previous state-of-the-art model on the NCBI dataset.
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