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Register a new userExtracting Business Process Models from Natural Language Texts
استخلاص مخططات إجراءات العمل انطلاقا من النصوص
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نقترح في هذه الأطروحة منهجية لتوليد مخططات الإجراءات من النصوص تحاكي عملية الترجمة الآلية, حيث تعتمد المنهجية المقترحة أسلوب الترجمة بالنقل على أساس دلالي, حيث ستتم في المرحلة الأولى معالجة النص لاستخلاص المفاهيم الأساسية فيه و العلاقات الدلالية بين هذه المفاهيم بما يشكل شبكة مفاهيم concept map للنص .
In our work, we chose to follow semantic transfer based approach. Our approach consists of two main phases. The first phase, Natural Language Analysis phase, aims to analyze the text and extract the required knowledge from it. In addition to the syntactic analysis results, one of the main outputs for this phase is a concept map which summarize the concepts of the related domain and the relationships between these concepts.
Artificial intelligence review:
Research summary
تُعنى هذه الأطروحة بتطوير منهجية لاستخلاص مخططات إجراءات العمل من النصوص الطبيعية باستخدام تقنيات الترجمة الآلية. تتضمن المنهجية مرحلتين رئيسيتين: الأولى هي تحليل النصوص الطبيعية لاستخلاص المفاهيم والعلاقات الدلالية بينها، والثانية هي توليد مخطط BPMN بناءً على التمثيل الدلالي المستخلص. تم اختبار المنهجية باستخدام مجموعة من النصوص والنماذج المستخلصة يدويًا، وأظهرت النتائج أن المنهجية المقترحة تفوقت على المنهجيات السابقة بنسبة تشابه وصلت إلى 81.21%.
Critical review
تُعد هذه الأطروحة خطوة مهمة نحو تحسين عملية نمذجة إجراءات العمل، إلا أنه يمكن تحسينها بشكل أكبر من خلال معالجة بعض النقاط. أولاً، تعتمد المنهجية بشكل كبير على دقة التحليل النحوي والصرفي، مما يجعلها عرضة للأخطاء في حال كانت هذه التحليلات غير دقيقة. ثانيًا، يمكن تحسين دقة فك غموض حالات الإحالة من خلال استخدام تقنيات تعلم الآلة المتقدمة. ثالثًا، يمكن توسيع نطاق الاختبارات لتشمل نصوصًا من لغات مختلفة لضمان عمومية المنهجية.
Questions related to the research
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ما هي المراحل الرئيسية في المنهجية المقترحة لاستخلاص مخططات إجراءات العمل من النصوص؟
تتضمن المنهجية مرحلتين رئيسيتين: الأولى هي تحليل النصوص الطبيعية لاستخلاص المفاهيم والعلاقات الدلالية بينها، والثانية هي توليد مخطط BPMN بناءً على التمثيل الدلالي المستخلص.
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ما هي نسبة التشابه التي حققتها المنهجية المقترحة مقارنة بالمنهجيات السابقة؟
حققت المنهجية المقترحة نسبة تشابه وصلت إلى 81.21%، متفوقة على المنهجيات السابقة التي حققت نسبة تشابه بلغت 76.98%.
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ما هي التحديات الرئيسية التي تواجه المنهجية المقترحة؟
التحديات الرئيسية تشمل دقة التحليل النحوي والصرفي، دقة فك غموض حالات الإحالة، وضرورة توسيع نطاق الاختبارات لتشمل نصوصًا من لغات مختلفة.
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كيف يمكن تحسين دقة فك غموض حالات الإحالة في المنهجية المقترحة؟
يمكن تحسين دقة فك غموض حالات الإحالة من خلال استخدام تقنيات تعلم الآلة المتقدمة والاستفادة من المزيد من البيانات التدريبية لتحسين النموذج.
References used
Abney, S. (1996). Partial parsing via finite-state cascades. Natural Language Engineering, 2(4), 337-344
Achour, C. B. (1998). Guiding scenario authoring. In In: 8th European-Japanese Conference on Information Modelling and Knowledge Bases
Blumberg, R., & Atre, S. (2003). The problem with unstructured data. Dm Review, 13(42-49), 62
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