Weighted entity linking and integration algorithm for medical knowledge graph generation
المؤلفون المشاركون
Shaban, Iman
Tantawi, Manal
Maghawiri, Nura
Imarah, Karim
المصدر
International Journal of Intelligent Computing and Information Sciences
العدد
المجلد 23، العدد 1 (31 مارس/آذار 2023)، ص ص. 1-17، 17ص.
الناشر
جامعة عين شمس كلية الحاسبات و المعلومات
تاريخ النشر
2023-03-31
دولة النشر
مصر
عدد الصفحات
17
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الموضوعات
الملخص EN
Semantic data integration is the process of interrelating information from multiple heterogeneous resources.
there is a need for representing data concepts and their relationships to eliminate heterogeneity among different data sources in healthcare management systems.
standardized medical ontologies provide predefined medical vocabulary serving as a stable interface for concepts related to medical data sources.
however, different ontologies have different concepts although these concepts have logical relations between them such as the human disease ontology and the symptoms ontology.
there aroused a need for a knowledge graph providing a reliable knowledge base for any intelligent healthcare expert advisor disease prediction system.
the knowledge graph provides a model for linking and integrating different concepts having logical relationships such as diseases and their symptoms.
medical online website and encyclopedia provides a reliable source for building such a knowledge graph.
the knowledge graph is enriched with social networks data where information extracted reflects a major source of data based on user experiences.
the paper proposes a framework for constructing a disease-symptom entity linked knowledge graph based on online medical encyclopedia and social networks user experiences.
entity linking such an integrated knowledge graph with standardized medical ontologies makes it a reliable knowledge base for a standard system that could be used by social networks user and the professional staff.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Maghawiri, Nura& Tantawi, Manal& Shaban, Iman& Imarah, Karim. 2023. Weighted entity linking and integration algorithm for medical knowledge graph generation. International Journal of Intelligent Computing and Information Sciences،Vol. 23, no. 1, pp.1-17.
https://search.emarefa.net/detail/BIM-1460747
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Maghawiri, Nura…[et al.]. Weighted entity linking and integration algorithm for medical knowledge graph generation. International Journal of Intelligent Computing and Information Sciences Vol. 23, no. 1 (Mar. 2023), pp.1-17.
https://search.emarefa.net/detail/BIM-1460747
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Maghawiri, Nura& Tantawi, Manal& Shaban, Iman& Imarah, Karim. Weighted entity linking and integration algorithm for medical knowledge graph generation. International Journal of Intelligent Computing and Information Sciences. 2023. Vol. 23, no. 1, pp.1-17.
https://search.emarefa.net/detail/BIM-1460747
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 15-17
رقم السجل
BIM-1460747
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر