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A machine learning approach for the curation of biomedical literature
2002
SIGKDD Explorations
In this paper, we present an automated text classification system for the classification of biomedical papers. This classification is based on whether there is experimental evidence for the expression of molecular gene products for specified genes within a given paper. The system performs pre-processing and data cleaning, followed by feature extraction from the raw text. It subsequently classifies the paper using the extracted features with a Naïve Bayes Classifier. Our approach has made it
doi:10.1145/772862.772875
fatcat:vhezxpubqvcupdg5qcbnuclfca