Information Retrieval
International Journal of Data Mining and Bioinformatics
Inter-species normalization of gene mentions with GNAT
Bioinformatics
High-performance gene name normalization with GeNo
Bioinformatics
Clinical text classification under the Open and Closed Topic Assumptions
International Journal of Data Mining and Bioinformatics
TX task: automatic detection of focus organisms in biomedical publications
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
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The gene ambiguity with the highest dimension is the species with which an entity is associated in biomedical text mining. Furthermore, one of the bottlenecks in gene normalisation is focus species detection. This study presents a method which is robust for all types of articles, particularly those without explicit species mentions. Since our method requires a training corpus, we developed an iterative distillation method to extend the corpus. Unsupervised corpus is therefore helpful for the detection of focus species. In experiments, the proposed method achieved a high accuracy of 85.64% and 84.32% in datasets with and without species mentions respectively.