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Building a protein name dictionary from full text: a machine learning term extraction approach-1

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posted on 2011-12-31, 05:16 authored by Lei Shi, Fabien Campagne

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Taken from "Building a protein name dictionary from full text: a machine learning term extraction approach"

BMC Bioinformatics 2005;6():88-88.

Published online 7 Apr 2005

PMCID:PMC1090555.

t had scores immediately greater than the value, and evaluated if the term referred to a gene or gene product in the article where the prediction was made. Precision of the prediction was calculated as the number of correct predictions over the total number of predictions (50). The 500 names which were checked represent a random sample of 21,501 names in the catalog. The Figure shows that predictions made with higher scores have a greater probability to be correct. The label shown for each evaluation point indicates the percentage of terms found in the evaluation corpus with a score above the score of this specific point.