إن التنبؤ بصعوبة المفردات الخاصة بالمجال هي مهمة مهمة نحو فهم أفضل للنطاق، وتعزيز التواصل بين الأشخاص الخبراء والخبراء.نقوم بالتحقيق في مركبات الأسماء المغلقة الألمانية والتركيز على تفاعل الميزات المعجمية القائمة على المركب (مثل التردد والإنتاجية) والميزات المستندة إلى المصطلحات (المتناقضة لغة خاصة بالمجال واللغة العامة) عبر تمثيلات الكلمات والصفوفات المصنفة.تكمل تجارب التنبؤ لدينا رؤى من التصنيف باستخدام (أ) ميزات مصممة يدويا لتوصيف الوالدين وتشكيل المركب و (ب) مجمعات Word Adgentdings.نجد أنه بالنسبة للتمييز الثنائي الواسع في التردد المركزي باللغة العامة "VS. الصعب الصعب" كافية، ولكن بالنسبة للتمييز الأكثر غرامة من أربعة فئات من الدرجة الأولى، فمن الأهمية بمكان تضمين ميزات الحد من الناحية المتعاوية والمركب والميزات المكونة.
Predicting the difficulty of domain-specific vocabulary is an important task towards a better understanding of a domain, and to enhance the communication between lay people and experts. We investigate German closed noun compounds and focus on the interaction of compound-based lexical features (such as frequency and productivity) and terminology-based features (contrasting domain-specific and general language) across word representations and classifiers. Our prediction experiments complement insights from classification using (a) manually designed features to characterise termhood and compound formation and (b) compound and constituent word embeddings. We find that for a broad binary distinction into easy' vs. difficult' general-language compound frequency is sufficient, but for a more fine-grained four-class distinction it is crucial to include contrastive termhood features and compound and constituent features.
References used
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