Recently, various methods were developed in order to solve the lexical ambiguity problem. Tagging system is a product of disambuguation studies. There is CLAWS as a practical tagging system, as well as the algorithms suggested by Church and DeRose.
These systems give good results in accuracy and speed. But applying them to Korean language raises many problems. Any tagging system for Korean is not yet developed. The use of Hidden Markov Model and some linguistic assumption for the assignment of part-of-speech tags can be a solution to the problem in fitting tagging model to Korean language. This thesis introduces some existing systems and explains a tagging algorithm and a tagging system that fits well to Korean language.
