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Register a new userFuzzyBIO: A Proposal for Fuzzy Representation of Discontinuous Entities
fuzzybio: اقتراح لتمثيل غامض للكيانات المتساقطة
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تشكل الكيانات المتساقطة تحديا للتعرف على الكيان المسمى (NER). تحدث هذه الظواهر عادة في المجال الطبي الطبيعي. كحل، يتم استخدام توسعات مخطط التمثيل الحيوي الذي يمكنه التعامل مع أنواع هذه أنواع الكيان بشكل شائع (I.E. BIOHD). ومع ذلك، فإن أنواع العلامات الإضافية تجعل مهمة NER أكثر صعوبة في التعلم. في هذه الورقة نقترحنا بديلا؛ مخطط حيوي مستمر غامض (Fuzzybio). نحن نركز على مهمة استخراج استجابة المخدرات الضارة والتطبيع لمقارنة Fuzzybio إلى BIOHD. نجد أن Fuzzybio يحسن استدعاء NER لشخصين من ثلاثة مجموعات بيانات ونتائج أعلى نسبة أعلى من الكيانات المفككة والمركبة المحددة بشكل صحيح لجميع مجموعات البيانات. يؤدي استخدام FuzzyBio أيضا إلى تحسين الأداء المنتهي للكيانات المستمرة والمركبة في مجموعتين من مجموعات البيانات الثلاثة. نظرا لأن Fuzzybio يحسن الأداء لبعض مجموعات البيانات والتحويل من Biohd إلى Fuzzybio واضح، فإننا نوصي بالتحقيق الأكثر فعالية لأي مجموعة بيانات تحتوي على كيانات متقطعة.
Discontinuous entities pose a challenge to named entity recognition (NER). These phenomena occur commonly in the biomedical domain. As a solution, expansions of the BIO representation scheme that can handle these entity types are commonly used (i.e. BIOHD). However, the extra tag types make the NER task more difficult to learn. In this paper we propose an alternative; a fuzzy continuous BIO scheme (FuzzyBIO). We focus on the task of Adverse Drug Response extraction and normalization to compare FuzzyBIO to BIOHD. We find that FuzzyBIO improves recall of NER for two of three data sets and results in a higher percentage of correctly identified disjoint and composite entities for all data sets. Using FuzzyBIO also improves end-to-end performance for continuous and composite entities in two of three data sets. Since FuzzyBIO improves performance for some data sets and the conversion from BIOHD to FuzzyBIO is straightforward, we recommend investigating which is more effective for any data set containing discontinuous entities.
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