Automatic Processing of Predicative Nouns for Korean Semantic Recognition
Suk-eui Lee, Soojong Lim · Korean Linguistics · 2018
This paper proposed a method of semantic recognition to improve the extraction of correct answers of the Q&A system through machine learning. For this purpose, the semantic recognition method is described based on the distribution of predicative nouns. Predicative noun vocabularies and sentences were collected from Wikipedia documents. The predicative nouns are typed by analyzing the environment in which the predicative nouns appear in sentences. This paper proposes a semantic recognition method of predicative nouns to which rules can be applied. In Chapter 2, previous studies on predicative nouns were reviewed. Chapter 3 explains how predicative nouns are distributed. In this paper, every predicative nouns that can not be processed by rules are excluded, therefore, the predicative nouns noun forms combined with the case marker ‘의’ were excluded. In Chapter 4, we extracted 728 sentences composed of 10,575 words from Wikipedia. A semantic analysis engine tool of ETRI was used and presented a predicative nouns noun that can be handled semantic recognition language.