Automatic text analysis tools have significant potential to improve the productivity of those who organise large collections of data. However, to be effective, they have to be both technically efficient and provide a productive interaction with the user. Geographic referencing of historical botanical data is difficult, time consuming and relies heavily on the expertise of the curators. Botanical specimens that have poor quality labelling are often disregarded and the information is lost. This work highlights how the use of automated analysis methods can be used to assist in the curation of a botanical specimen library. © 2012 Springer-Verlag.
CITATION STYLE
Llewellyn, C., Grover, C., Oberlander, J., & Haston, E. (2012). Enhancing the curation of botanical data using text analysis tools. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7489 LNCS, pp. 480–485). https://doi.org/10.1007/978-3-642-33290-6_55
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