期刊名称：International Journal of Data Mining & Knowledge Management Process
印刷版ISSN：2231-007X
电子版ISSN：2230-9608
出版年度：2016
卷号：6
期号：3
页码：11
DOI：10.5121/ijdkp.2016.6302
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：The biomedical research literature is one among many other domains that hides a precious knowledge, andthe biomedical community made an extensive use of this scientific literature to discover the facts ofbiomedical entities, such as disease, drugs,etc.MEDLINE is a huge database of biomedical researchpapers which remain a significantly underutilized source of biological information. Discovering the usefulknowledge from such huge corpus leads to various problems related to the type of information such as theconcepts related to the domain of texts and the semantic relationship associated with them. In this paper,we propose a Two-level model for Self-supervised relation extraction from MEDLINE using UnifiedMedical Language System (UMLS) Knowledge base. The model uses a Self-supervised Approach forRelation Extraction (RE) by constructing enhanced training examples using information from UMLS. Themodel shows a better result in comparison with current state of the art and naïve approaches.
