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Learning Relations and Information Extraction Rules for Protein Annotation
Niagara Falls, Ontario, Canada May 21-May 23
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AINAW.2007.22021st International Conference on Adva ...
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Jee-Hyub Kim, University of Geneva, Switzerland
Melanie Hilario, University of Geneva, Switzerland
Protein annotation is a task that describes protein X in terms of topic Y. Until now, most of protein annotation work has been done manually by human annotators. However, as the number of biomedical papers grows ever rapidly, manual annotation becomes difficult, and there is increasing need to automate the protein annotation process. Recently, Information Extraction (IE) has been used to solve this problem. Typically, IE requires pre-defined relations and hand-crafted IE rules or annotated corpora, and these requirements are difficult to satisfy in real world domains such as the biomedical domain. In this paper, we describe an IE system which requires only sentences labeled relevant or not to a given topic by domain experts.
Citation:
Jee-Hyub Kim, Melanie Hilario, "Learning Relations and Information Extraction Rules for Protein Annotation," ainaw, vol. 1, pp.349-354, 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07), 2007
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