Abstract
OSCAR3 is an open extensible system for the automated annotation of chemistry in scientific articles, which can process thousands of articles per hour. This XML annotation supports applications such as interactive browsing and chemically-aware searching, and has been designed for integration with larger text-analysis systems. We report its application to the high-throughput analysis of the small-molecule chemistry content of texts in life sciences, such as PubMed abstracts. © Springer-Verlag Berlin Heidelberg 2006.
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CITATION STYLE
Corbett, P., & Murray-Rust, P. (2006). High-throughput identification of chemistry in life science texts. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4216 LNBI, pp. 107–118). Springer Verlag. https://doi.org/10.1007/11875741_11
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