The nature of statistical learning theory
The nature of statistical learning theory
Information Retrieval
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Natural Language Engineering
Assigning function tags to parsed text
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
A memory-based approach to learning shallow natural language patterns
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
High precision extraction of grammatical relations
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
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This study aims to identify dependency structure in Korean sentences with the cascaded chunking strategy In the first stages of the cascade, we find chunks of NP and guess grammatical relations (GRs) using Support Vector Machine (SVM) classifiers for every possible modifier-head pairs of chunks in terms of GR categories as subject, object, complement, adverbial, and etc In the next stage, we filter out incorrect modifier-head relations in each cascade for its corresponding GR using the SVM classifiers and the characteristics of the Korean language such as distance, no-crossing and case property Through an experiment with a tree and GR tagged corpus for training the proposed parser, we achieved an overall accuracy of 85.7% on average.