• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.395-399
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• 2009

In this work, we describe the syntactic tag prediction system for Korean using the decision tree and CRFs. Generally they select features by their intuition. It depends on their prior knowledge. In this works, we combine features systematically using the decision tree. We also analyze errors and optimize features for the best performance. From the result of experiments, we can see that the proposed method is effective for the syntactic tag estimation and will be helpful for the syntactic analysis.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.103-111
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• 2010

Syntactic analysis is an important step in natural language processing. However, we cannot use the syntactic analyzer in Korean for low performance and without robustness. We propose new robust, high speed and high performance Korean syntactic analyzer using CRFs. We treat a parsing problem as a labeling problem. We use a cascaded chunking for Korean parsing. We label syntactic information to each Eojeol at each step using CRFs. CRFs use part-of-speech tag and Eojeol syntactic tag features. Our experimental results using 10-fold cross validation show significant improvement in the robustness, speed and performance of long Korea sentences.