Paper: Probabilistic Models for Korean Morphological Analysis

ACL ID I05-2034
Title Probabilistic Models for Korean Morphological Analysis
Venue International Joint Conference on Natural Language Processing
Session poster-demo-tutorial
Year 2005
Authors

This paper discusses Korean morpho- logical analysis and presents three probabilistic models for morphological analysis. Each model exploits a distinct linguistic unit as a processing unit. The three models can compensate for each other’s weaknesses. Contrary to the previous systems that depend on man- ually constructed linguistic knowledge, the proposed system can fully automat- ically acquire the linguistic knowledge from annotated corpora (e.g. part-of- speech tagged corpora). Besides, with- out any modification of the system, it can be applied to other corpora having different tagsets and annotation guide- lines. We describe the models and present evaluation results on three cor- pora with a wide range of conditions.