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BMCBI
2008

All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning

8 years 8 months ago
All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning
Background: Automated extraction of protein-protein interactions (PPI) is an important and widely studied task in biomedical text mining. We propose a graph kernel based approach for this task. In contrast to earlier approaches to PPI extraction, the introduced all-paths graph kernel has the capability to make use of full, general dependency graphs representing the sentence structure. Results: We evaluate the proposed method on five publicly available PPI corpora, providing the most comprehensive evaluation done for a machine learning based PPI-extraction system. We additionally perform a detailed evaluation of the effects of training and testing on different resources, providing insight into the challenges involved in applying a system beyond the data it was trained on. Our method is shown to achieve state-of-the-art performance with respect to comparable evaluations, with 56.4 F-score and 84.8 AUC on the AImed corpus. Conclusion: We show that the graph kernel approach performs on st...
Antti Airola, Sampo Pyysalo, Jari Björne, Tap
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2008
Where BMCBI
Authors Antti Airola, Sampo Pyysalo, Jari Björne, Tapio Pahikkala, Filip Ginter, Tapio Salakoski
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