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Register a new userChallenging distributional models with a conceptual network of philosophical terms
النماذج التوزيعية الصعبة مع شبكة مفاهيمية من المصطلحات الفلسفية
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ألهمت البحوث اللغوية الحسابية على تغيير اللغة من خلال نماذج التوزيع الدلالي (DS) باحثين من مجالات مثل الفلسفة والدراسات الأدبية، الذين يستخدمون هذه الأساليب لاستكشاف ومقارنة مجموعات البيانات الصغيرة النسبية نسبيا تحليلها تقليديا عن طريق القراءة الدقيقة.لا يزال البحث في أساليب البيانات الصغيرة في المراحل المبكرة وليس من الواضح الطرق التي تحقق أفضل النتائج.نحن نبحث في إمكانيات وقيود استخدام النماذج الدلالية التوزيعية لتحليل البيانات الفلسفية عن طريق حالة استخدام واقعية.نحن نقدم حقيقة أرضية للتقييم التي أنشأتها خبراء الفلسفة ومخطط لاستخدام نماذج DS في إعداد منهجي سليم.نقارن ثلاث طرق لإنشاء نماذج متخصصة من مجموعات البيانات الصغيرة.على الرغم من أن النماذج لا تؤدي بشكل جيد بما يكفي لدعم الفلاسفة مباشرة، إلا أننا نجد أن النماذج المصممة لإنتاج البيانات الصغيرة واعدة في العمل في المستقبل.
Computational linguistic research on language change through distributional semantic (DS) models has inspired researchers from fields such as philosophy and literary studies, who use these methods for the exploration and comparison of comparatively small datasets traditionally analyzed by close reading. Research on methods for small data is still in early stages and it is not clear which methods achieve the best results. We investigate the possibilities and limitations of using distributional semantic models for analyzing philosophical data by means of a realistic use-case. We provide a ground truth for evaluation created by philosophy experts and a blueprint for using DS models in a sound methodological setup. We compare three methods for creating specialized models from small datasets. Though the models do not perform well enough to directly support philosophers yet, we find that models designed for small data yield promising directions for future work.
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