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A study of some of the of the Verbs’ Arabic Roots in the stories of Osman Ceviksoy Like a Voice in The Dark.: Osman Çeviksoy'un "Karanlıkta Ses Gibi" Başlıklı Öykü Kitabında Arapça Kökenli Türkçe Fillerin İncelenmesi
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Due to the Geographical links, language is one of the multiple affects among Arabs and Turks. As the different studies demonstrate, Turkish contains many words derived from other languages, yet Arabic remains the language that has great affects on Turkish. Unlike Turkish language, Arabic is a derivative language that requires no suffixes. Thus, Arabic verbs are tuned into Turkish verbs by adding auxiliary verbs. The present study traces some of the Turkish compound words of Arabic roots with an explanation that shows the Auxiliary added to form the Turkish verb as found in the stories of Otman Chevek Sawy’s Like A voice in the Dark. The conclusion sums up the findings of the study illustrated by numbers.

Özet

Uzun yıllar aynı coğrafyada yaşayan Türkler ve Araplar arasında birçok alanda olduğu gibi dilde de etkileşim yaşandığı bilinmektedir. Birçok çalışmada da tespit edildiği gibi Türkçeye birçok yabancı dilden kelime girmiştir; ancak bunların başında Arapça olduğu söylenebilir. Arapçadan Türkçeye giren kelimler mastar olarak girdiği için Türkçeden yardımcı fiil alarak fiille dönüşmüştür. Arapça bükümlü bir dil olmasından dolayı içinde durum ekleri bulunmamaktadır. Türkçede durumun bunun tam tersidir. Çünkü fiiller belirli bir durumu ekini isterler. Bu çalışmada Osman Çeviksoy'un "Karanlıkta Ses Gibi" Başlıklı Öykü Kitabında yer alan metinlerde geçen Arapça kökenli kelimelerle inşa edilen birleşik fiiller tek tek tespit edilmiş, satır ve sayfa numaraları belirtilmiş; nasıl oluştuğu ve hangi yardımcı fiili aldığı belirlenmiştir. Çalışmanın sonunda elde edilen sonuç rakamlarla tasnif edilerek belirilmeye çalışılmıştır.

 

      

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Wed Dec 30 2020
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Text documents are unstructured and high dimensional. Effective feature selection is required to select the most important and significant feature from the sparse feature space. Thus, this paper proposed an embedded feature selection technique based on Term Frequency-Inverse Document Frequency (TF-IDF) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) for unstructured and high dimensional text classificationhis technique has the ability to measure the feature’s importance in a high-dimensional text document. In addition, it aims to increase the efficiency of the feature selection. Hence, obtaining a promising text classification accuracy. TF-IDF act as a filter approach which measures features importance of the te

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