Making large-scale support vector machine learning practical
Advances in kernel methods
Extracting complex biological events with rich graph-based feature sets
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing: Shared Task
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Overview of BioNLP Shared Task 2011
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
Overview of Genia event task in BioNLP Shared Task 2011
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
BioNLP Shared Task 2011: supporting resources
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
Overview of Genia event task in BioNLP Shared Task 2011
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
Overview of the entity relations (REL) supporting task of BioNLP Shared Task 2011
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
BioNLP Shared Task 2011: supporting resources
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
New resources and perspectives for biomedical event extraction
BioNLP '12 Proceedings of the 2012 Workshop on Biomedical Natural Language Processing
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This paper presents our approach (referred to as BioEvent) for protein-level complex event extraction, developed for the GENIA task (Kim et al., 2011b) of the BioNLP Shared Task 2011 (Kim et al., 2011a). We developed a double layered machine learning approach which utilizes a state-of-the-art minimized feature set for each of the event types. We improved the best performing system of BioNLP 2009 overall, and ranked first amongst 15 teams in finding "Localization" events in 2011. BioEvent is available at http://bioevent.sourceforge.net/