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Register a new userClassifying Dyads for Militarized Conflict Analysis
تصنيف الصقيع لتحليل الصراع العسكري
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إن فهم أصول الصراع العسكري هو تعهد معقد، لكنه مهم للغاية. تسعى البحوث الحالية إلى بناء هذا الفهم من خلال النظر في علاقات ثنائية جانبية بين أزواج الكيان (الأسباب الضاغطة) والعلاقات متعددة الأطراف بين كيانات متعددة (الأسباب الجهازية). الهدف من هذا العمل هو مقارنة هذين الأسباب من حيث ما يرتبط به مع الصراع بين كيانين. نقوم بذلك عن طريق وضع مجموعة من الميزات النصية والرسوم البيانية التي تمثل كل من الأسباب. يتم استخراج الميزات من ويكيبيديا وأمتصاص الرسم بياني كبير. تمثل العقد في هذا الرسم البياني الكيانات المرتبطة بالحواف المسمى التي تمثل حليف أو علاقات العدو. يسمح ذلك بإلقاء المشكلة كمرافقة تصنيف حافة، والتي نعلم تصنيف DYAD. نقترح وتقييم المصنفين لتحديد ما إذا كان زوج معين من الكيانات حلفاء أو أعداء. تشير نتائجنا إلى أن ميزاتنا المنهجية قد تكون أفضل قليلا ترتبط بالصراع. علاوة على ذلك، نجد أن مقالات حلفاء ويكيبيديا أكثر شهرة من الأعداء.
Understanding the origins of militarized conflict is a complex, yet important undertaking. Existing research seeks to build this understanding by considering bi-lateral relationships between entity pairs (dyadic causes) and multi-lateral relationships among multiple entities (systemic causes). The aim of this work is to compare these two causes in terms of how they correlate with conflict between two entities. We do this by devising a set of textual and graph-based features which represent each of the causes. The features are extracted from Wikipedia and modeled as a large graph. Nodes in this graph represent entities connected by labeled edges representing ally or enemy-relationships. This allows casting the problem as an edge classification task, which we term dyad classification. We propose and evaluate classifiers to determine if a particular pair of entities are allies or enemies. Our results suggest that our systemic features might be slightly better correlates of conflict. Further, we find that Wikipedia articles of allies are semantically more similar than enemies.
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This study aims to determine the difference of householder spending values between the Syrian provinces. It also aims to find out which of the components and the various items of expenditure, that contributed significantly to the occurrence of this d
ifference and disparity between provinces , where cluster analysis method was used to find out this difference and classification .
The most important results that have been reached: The result of cluster analysis is that there are three groups of Syrian provinces , the first group included the provinces of high householder spending such as Damascus province , the second group included the provinces of medium householder spending such as: Rural Damascus , Homs , Tartus , Lattakia , Al-Sweida , Daraa , Al – Quneitra .
The third group included the provinces of low householder spending such as: Hama , Idleb , Aleppo , Al-Rakka , Deir-ez-Zor , Al-Hasakeh .
Accordingly , that most important components and variables of householder spending, which contributed to the classification of the Syrian provinces of homogeneous groups are spending on housing , spending on education , spending on health , spending on transport and communications .
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important and longest of these conflicts that have to control the most
important cities such
as Damascus and Edessa and Akadds.othml Arabs living there the horrors of those
conflicts and suffered a lot, the Persian Empire has taken Arabs in Iraq Manathira shield
shielding them Byzantines attacks as well as from the Byzantines took Ghassanid living in
Syria shield shielding them Persians attacks and have been associated with them Bohlav
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