The relationship between recall and precision
Journal of the American Society for Information Science
The nature of statistical learning theory
The nature of statistical learning theory
Making large-scale support vector machine learning practical
Advances in kernel methods
A statistical learning learning model of text classification for support vector machines
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
The Frame-Based Module of the SUISEKI Information Extraction System
IEEE Intelligent Systems
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Genescene: biomedical text and data mining
Proceedings of the 3rd ACM/IEEE-CS joint conference on Digital libraries
Extracting Biochemical Interactions from MEDLINE Using a Link Grammar Parser
ICTAI '03 Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence
A shallow parser based on closed-class words to capture relations in biomedical text
Journal of Biomedical Informatics
A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs
The Journal of Machine Learning Research
RelEx---Relation extraction using dependency parse trees
Bioinformatics
Exploiting the contextual cues for bio-entity name recognition in biomedical literature
Journal of Biomedical Informatics
BioPPIExtractor: A protein-protein interaction extraction system for biomedical literature
Expert Systems with Applications: An International Journal
IntEx: a syntactic role driven protein-protein interaction extractor for bio-medical text
ISMB '05 Proceedings of the ACL-ISMB Workshop on Linking Biological Literature, Ontologies and Databases: Mining Biological Semantics
Comparative experiments on learning information extractors for proteins and their interactions
Artificial Intelligence in Medicine
Developing a robust part-of-speech tagger for biomedical text
PCI'05 Proceedings of the 10th Panhellenic conference on Advances in Informatics
DTMBIO '10 Proceedings of the ACM fourth international workshop on Data and text mining in biomedical informatics
Multiple kernel learning in protein-protein interaction extraction from biomedical literature
Artificial Intelligence in Medicine
Using a shallow linguistic kernel for drug-drug interaction extraction
Journal of Biomedical Informatics
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Protein-protein interactions play a key role in various aspects of the structural and functional organization of the cell. Knowledge about them unveils the molecular mechanisms of biological processes. However, the amount of biomedical literature regarding protein interactions is increasing rapidly and it is difficult for interaction database curators to detect and curate protein interaction information manually. This paper presents a SVM-based system, named BioPPISVMExtractor, to identify protein-protein interactions in biomedical literature. This system uses rich feature sets including word features, keyword feature, protein names distance feature and Link path feature for SVM classification. In addition, the Link Grammar extraction result feature is introduced to improve the precision rate. Experimental evaluations with other state-of-the-art PPI extraction systems tested on the DIP corpus indicate that BioPPISVMExtractor can substantially improve recall at the cost of a moderate decline in precision.