Pum-Mo Ryu


2022

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Proceedings of the 29th International Conference on Computational Linguistics
Nicoletta Calzolari | Chu-Ren Huang | Hansaem Kim | James Pustejovsky | Leo Wanner | Key-Sun Choi | Pum-Mo Ryu | Hsin-Hsi Chen | Lucia Donatelli | Heng Ji | Sadao Kurohashi | Patrizia Paggio | Nianwen Xue | Seokhwan Kim | Younggyun Hahm | Zhong He | Tony Kyungil Lee | Enrico Santus | Francis Bond | Seung-Hoon Na
Proceedings of the 29th International Conference on Computational Linguistics

2014

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Sentential Paraphrase Generation for Agglutinative Languages Using SVM with a String Kernel
Hancheol Park | Gahgene Gweon | Ho-Jin Choi | Jeong Heo | Pum-Mo Ryu
Proceedings of the 28th Pacific Asia Conference on Language, Information and Computing

2006

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Compiling large language resources using lexical similarity metrics for domain taxonomy learning
Ronny Melz | Pum-Mo Ryu | Key-Sun Choi
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

In this contribution we present a new methodology to compile large language resources for domain-specific taxonomy learning. We describe the necessary stages to deal with the rich morphology of an agglutinative language, i.e. Korean, and point out a second order machine learning algorithm to unveil term similarity from a given raw text corpus. The language resource compilation described is part of a fully automatic top-down approach to construct taxonomies, without involving the human efforts which are usually required.

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Taxonomy Learning using Term Specificity and Similarity
Pum-Mo Ryu | Key-Sun Choi
Proceedings of the 2nd Workshop on Ontology Learning and Population: Bridging the Gap between Text and Knowledge

2004

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Determining the Specificity of Terms based on Information Theoretic Measures
Pum-Mo Ryu | Key-Sun Choi
Proceedings of CompuTerm 2004: 3rd International Workshop on Computational Terminology

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Determining the Specificity of Terms using Compositional and Contextual Information
Pum-Mo Ryu
Proceedings of the ACL Student Research Workshop