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Register a new userGenerating An Optimal Interview Question Plan Using A Knowledge Graph And Integer Linear Programming
إنشاء خطة سؤال مقابلة مثالية باستخدام رسم بياني للمعرفة والبرمجة الخطية الصحيحة
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بالنظر إلى تنوع المرشحين وتعقيد متطلبات الوظائف، ومنذ إجراء المقابلات عملية ذاتية بطبيعتها، فهي مهمة مهمة لضمان مقابلات متسقة وعيائية وفعالة وموضوعية تؤدي إلى توظيف عالي الجودة. نقترح نظام مساعد مقابلة تلقائيا، وبطريقة موضوعية، حدد مجموعة مثالية من الأسئلة الفنية (من بنك الأسئلة) المخصصة للمرشح. يمكن أن تساعد هذه المجموعة مقابلة بشريا في التخطيط لمقابلة قادمة في هذا المرشح. نحن نقوم بإضفاء الطابع الرسمي على مشكلة اختيار مجموعة من الأسئلة كمشكلة برمجة خطية عددا صحيحة واستخدام الحلفل القياسي للحصول على حل. نحن نستخدم الرسم البياني المعرفة كمعرفة خلفية في هذه الصيغة، واستقبال وظائفنا الموضوعية والقيود منه. نحن نستخدم السيرة الذاتية للمرشح لتخصيص اختيار الأسئلة. نقترح تقييم جوهري لمقارنة مجموعة من الأسئلة المقترحة مع أسئلة طرحت بالفعل. نحن نستخدم أيضا المقابلات الخبراء لتقييم نهجنا بشكل نسبيا مع مجموعة من خطوط الأساس المعقولة.
Given the diversity of the candidates and complexity of job requirements, and since interviewing is an inherently subjective process, it is an important task to ensure consistent, uniform, efficient and objective interviews that result in high quality recruitment. We propose an interview assistant system to automatically, and in an objective manner, select an optimal set of technical questions (from question banks) personalized for a candidate. This set can help a human interviewer to plan for an upcoming interview of that candidate. We formalize the problem of selecting a set of questions as an integer linear programming problem and use standard solvers to get a solution. We use knowledge graph as background knowledge in this formulation, and derive our objective functions and constraints from it. We use candidate's resume to personalize the selection of questions. We propose an intrinsic evaluation to compare a set of suggested questions with actually asked questions. We also use expert interviewers to comparatively evaluate our approach with a set of reasonable baselines.
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This work deals with a new method for solving Integer Linear Programming Problems depending on a previous methods for solving these problems, such that Branch and Bound method and Cutting Planes method where this new method is a combination between t
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