Making large-scale support vector machine learning practical
Advances in kernel methods
A metalearning approach to processing the scope of negation
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning
Learning the scope of negation in biomedical texts
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
NeSp-NLP '10 Proceedings of the Workshop on Negation and Speculation in Natural Language Processing
Learning the scope of negation via shallow semantic parsing
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Automatic extraction of lexico-syntactic patterns for detection of negation and speculation scopes
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
*SEM 2012 shared task: resolving the scope and focus of negation
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
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This paper describes our participation in the closed track of the *SEM 2012 Shared Task of finding the scope of negation. To perform the task, we propose a system that has three components: negation cue detection, scope of negation detection, and negated event detection. In the first phase, the system creates a lexicon of negation signals from the training data and uses the lexicon to identify the negation cues. Then, it applies machine learning approaches to detect the scope and negated event for each negation cue identified in the first phase. Using a preliminary approach, our system achieves a reasonably good accuracy in identifying the scope of negation.