A semi-supervised learning framework for biomedical eventextraction based on hidden topics
Conclusion: The results suggest that by incorporating un-annotated data, the proposed framework indeed improves the performance of the state-of-the-art event extraction system and the similarity between sentences might be precisely described by hidden topics and structures of the sentences.
Source: Artificial Intelligence in Medicine - Category: Bioinformatics Source Type: research
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