Recently, real documents such as newspapers as well as blogs include newly coined words such as "Wikipedia". However, most previous information processing technologies cannot deal with these newly coined words because they construct their dictionaries based on materials acquired during system development. In this paper, we propose a model to automatically recognize Korean unknown words excluded from the previously constructed dictionary. The proposed model consists of an unknown noun recognition phase based on full text analysis, an unknown verb recognition phase based on web document frequency, and an unknown noun recognition phase based on web document frequency. The proposed model can recognize accurately the unknown words occurred once and again in a document by the full text analysis. Also, the proposed model can recognize broadly the unknown words occurred once in the document by using web documents. Besides, the proposed model fan recognize both a Korean unknown verb, which syllables can be changed from its base form by inflection, and a Korean unknown noun, which syllables are not changed in any eojeol. Experimental results shows that the proposed model improves precision 1.01% and recall 8.50% as compared with a previous model.