Semisupervised Learning Based Disease-Symptom and Symptom-Therapeutic Substance Relation Extraction from Biomedical Literature
المؤلفون المشاركون
Yang, Zhihao
Feng, Qinlin
Gui, Yingyi
Wang, Lei
Li, Yuxia
المصدر
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-10-16
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
With the rapid growth of biomedical literature, a large amount of knowledge about diseases, symptoms, and therapeutic substances hidden in the literature can be used for drug discovery and disease therapy.
In this paper, we present a method of constructing two models for extracting the relations between the disease and symptom and symptom and therapeutic substance from biomedical texts, respectively.
The former judges whether a disease causes a certain physiological phenomenon while the latter determines whether a substance relieves or eliminates a certain physiological phenomenon.
These two kinds of relations can be further utilized to extract the relations between disease and therapeutic substance.
In our method, first two training sets for extracting the relations between the disease-symptom and symptom-therapeutic substance are manually annotated and then two semisupervised learning algorithms, that is, Co-Training and Tri-Training, are applied to utilize the unlabeled data to boost the relation extraction performance.
Experimental results show that exploiting the unlabeled data with both Co-Training and Tri-Training algorithms can enhance the performance effectively.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Feng, Qinlin& Gui, Yingyi& Yang, Zhihao& Wang, Lei& Li, Yuxia. 2016. Semisupervised Learning Based Disease-Symptom and Symptom-Therapeutic Substance Relation Extraction from Biomedical Literature. BioMed Research International،Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1097375
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Feng, Qinlin…[et al.]. Semisupervised Learning Based Disease-Symptom and Symptom-Therapeutic Substance Relation Extraction from Biomedical Literature. BioMed Research International No. 2016 (2016), pp.1-13.
https://search.emarefa.net/detail/BIM-1097375
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Feng, Qinlin& Gui, Yingyi& Yang, Zhihao& Wang, Lei& Li, Yuxia. Semisupervised Learning Based Disease-Symptom and Symptom-Therapeutic Substance Relation Extraction from Biomedical Literature. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1097375
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1097375
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