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An Experimental Study on the Relation Extraction from Biomedical Abstracts using Machine Learning
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 Title & Authors
An Experimental Study on the Relation Extraction from Biomedical Abstracts using Machine Learning
Choi, Sung-Pil;
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This paper introduces a relation extraction system that can be used in identifying and classifying semantic relations between biomedical entities in scientific texts using machine learning methods such as Support Vector Machines (SVM). The suggested system includes many useful functions capable of extracting various linguistic features from sentences having a pair of biomedical entities and applying them into training relation extraction models for maximizing their performance. Three globally representative collections in biomedical domains were used in the experiments which demonstrate its superiority in various biomedical domains. As a result, it is most likely that the intensive experimental study conducted in this paper will provide meaningful foundations for research on bio-text analysis based on machine learning.
Relation Extraction;Support Vector Machines;Protein-Protein Interaction Extraction;Text Mining;Machine Learning;
 Cited by
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