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Register a new userBootstrapping Multilingual Metadata Extraction: A Showcase in Cyrillic
استخراج البيانات الوصفية متعددة اللوزتين: عرض في السيريلية
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التطبيقات القائمة على البيانات العلمية هي ذات أهمية متزايدة من أي وقت مضى.ينتج عن هذا العيوب للمناطق التي لا تتوفر فيها بيانات عالية الجودة وأنظمة متوافقة، مثل المنشورات غير الإنجليزية.لتعزيز تخفيف هذا الخلل، نستخدم منشورات البرنامج النصي السيريلية من المجموعة الأساسية لإنشاء مجموعة بيانات عالية الجودة لاستخراج البيانات الوصفية.نستخدم بياناتنا للتدريب وتقييم نماذج وضع التسلسل لاستخراج معلومات العنوان والمؤلف.إعادة تدريب جروبيد على بياناتنا، نلاحظ تحسينات كبيرة من حيث الدقة وتذكر وتحقيق نتائج أفضل مع نموذج متطور بنفسي.نجعل بياناتنا مجموعة تغطي أكثر من 15000 منشورات بالإضافة إلى شفرة المصدر لدينا بحرية.
Applications based on scholarly data are of ever increasing importance. This results in disadvantages for areas where high-quality data and compatible systems are not available, such as non-English publications. To advance the mitigation of this imbalance, we use Cyrillic script publications from the CORE collection to create a high-quality data set for metadata extraction. We utilize our data for training and evaluating sequence labeling models to extract title and author information. Retraining GROBID on our data, we observe significant improvements in terms of precision and recall and achieve even better results with a self developed model. We make our data set covering over 15,000 publications as well as our source code freely available.
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