Text Mining in Full Text Articles—Methodical and Represenation Issues
Correspondence: (Login to view email address)
- Fraunhofer SCAI
PDF (1.3 MB)
- Document Type:
- Poster
- Date:
- Received 22 April 2009 15:25 UTC; Posted 22 April 2009
- Subjects:
- Bioinformatics
- Abstract:
In many cases, information from abstracts of biomedical publications is not sufficient for annotation of database entries. Therefore, text mining systems supporting curators of biodatabases should be able to process full text articles. Beside the technical problems arising from full text parsing, the representation of the annotated full text is an important issue. Journal articles are mostly electronically available in PDF or HTML format. Also with more easily manageable XML formats, readers would like to have a visualisation of annotations and semantic enrichment directly in the PDF or HTML. We summarize the technical problems arising from parsing of HTML and PDF journal full texts and show first results of visualisation in both formats.
- Collection:
- 3rd International Biocuration Conference
- Presented at:
- 3rd International Biocuration Conference, 16 April 2009
Discussion
- Votes:
-
2 votes
- Comments:
-
0 comments
- (Login to share with a colleague)
Additional information
- License:
- This document is licensed to the public under the Creative Commons Attribution 3.0 License
- How to cite this document:
-
Klinger, Roman, Pesch, Robert, Mevissen, Theo, and Fluck, Juliane. Text Mining in Full Text Articles—Methodical and Represenation Issues. Available from Nature Precedings <http://dx.doi.org/10.1038/npre.2009.3141.1> (2009)
- Version info:
-
Other versions of this document in Nature Precedings
None.
Other versions of this document elsewhere on the web
None known.
