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Register a new userAutomatic Discrimination between Inherited and Borrowed Latin Words in Romance Languages
التمييز التلقائي بين الكلمات اللاتينية الموروثة والمتوسطة في اللغات الرومانسية
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في هذه الورقة، نتعلم مشكلة التمييز تلقائيا بين الكلمات اللاتينية الموروثة والمتوسطة. نقدم مجموعة بيانات جديدة والتحقيق في حالة لغات الرومانسية (الرومانية والإيطالية والفرنسية والإسبانية والبرتغالية والكانتالينية)، حيث تورث الكلمات مباشرة من التعايش اللاتيني مع الكلمات المقترضة من اللاتينية، واستكشاف ما إذا كان من الممكن التمييز التلقائي بينهما. بعد أن دخلت اللغة في مرحلة لاحقة، لم تعد الكلمات المستعارة تخضع لقواعد تحول الصوت التاريخية، وبالتالي فهي من المفترض أنها أقل تآكل، وهذا هو السبب في أننا نتوقع منهم أن يكون لهم هيكل جوهري مختلف بوسائل حسابية. نحن نوظف العديد من نماذج التعلم الآلي للتمييز تلقائيا بين الكلمات الموروثة والمتعرضة ومقارنة أدائها مع مجموعات ميزة مختلفة. نقوم بتحليل القوة التنبؤية النماذج على نسختين من مجموعات البيانات والأكبر والفيديو. نحن أيضا التحقيق في ما إذا كانت المعرفة المسبقة بالمخلفات توفر نتائج أفضل، وتستخدم ميزات حرف N-Gram المستخرجة من أزواج Word-Entymon ومن محاذاةها.
In this paper, we address the problem of automatically discriminating between inherited and borrowed Latin words. We introduce a new dataset and investigate the case of Romance languages (Romanian, Italian, French, Spanish, Portuguese and Catalan), where words directly inherited from Latin coexist with words borrowed from Latin, and explore whether automatic discrimination between them is possible. Having entered the language at a later stage, borrowed words are no longer subject to historical sound shift rules, hence they are presumably less eroded, which is why we expect them to have a different intrinsic structure distinguishable by computational means. We employ several machine learning models to automatically discriminate between inherited and borrowed words and compare their performance with various feature sets. We analyze the models' predictive power on two versions of the datasets, orthographic and phonetic. We also investigate whether prior knowledge of the etymon provides better results, employing n-gram character features extracted from the word-etymon pairs and from their alignment.
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This research aimed to identify the discrimination capacity of the
part one of AAMR adaptive behavior scale in discrimination
between children from different ages, through studying the
differences between children's performance who including in th
e
research, where the research sample consisted of (490) children
aged (11-15) year, they are students in the second stage basic
teaching students in Damascus governorate schools.
This research aimed to identify the discrimination
capacity of the part one of AAMR adaptive behavior scale
in discrimination between children from different ages,
through studying the differences between children's
performance who including in t
he research, where the
research sample consisted of (490) children aged (11-15)
year, they are students in the second stage basic teaching
students in Damascus governorate schools.
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