تقدم هذه الورقة النتائج الأولية للمشروع الجاري الذي يحلل الجسم المتنامي للبحث العلمي الذي نشر حول جائحة CovID-19.في هذا البحث، يتم استخدام نموذج دلالي للأغراض العامة لتعليق دفعة من 500 جمل تم اختيارها يدويا من Cord-19 Corpus.بعد ذلك، تم تصميم وتقييم خط أنابيب تعدين النص الأساسي من خلال مجموعة كبيرة من جمل 100،959.نقدم تحليلا نوعيا للحقائق الأكثر إثارة للاهتمام استخراجها تلقائيا وتسليط الضوء على خطوط التنمية المستقبلية المحتملة.تظهر النتائج الأولية أن النماذج الدلالية للأغراض العامة هي أداة مفيدة لاكتشاف معرفة غرامة المحبوس في كورسا الوثائق العلمية الكبيرة.
This paper presents the preliminary results of an ongoing project that analyzes the growing body of scientific research published around the COVID-19 pandemic. In this research, a general-purpose semantic model is used to double annotate a batch of 500 sentences that were manually selected from the CORD-19 corpus. Afterwards, a baseline text-mining pipeline is designed and evaluated via a large batch of 100,959 sentences. We present a qualitative analysis of the most interesting facts automatically extracted and highlight possible future lines of development. The preliminary results show that general-purpose semantic models are a useful tool for discovering fine-grained knowledge in large corpora of scientific documents.
References used
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