• Language and Information
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• v.14 no.2
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• pp.33-46
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• 2010

This paper introduces a new linguistic-focused approach for sentiment analysis (SA) of Korean. In order to overcome shortcomings of previous works that focused mainly on statistical methods, we made effective use of various linguistic features reflecting the nature of Korean. These features include contextual shifters, modal affixes, and the morphological dependency of chunk structures. Moreover, in order to eschew possible confusion caused by ambiguous words and to improve the results of SA, we also proposed simple adjustment methods of word senses using KOLON ontology mapping information. Through experiments we contend that effective use of linguistic features and ontological information can improve the results of sentiment analysis of Korean.

• Korean Journal of Cognitive Science
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• v.3 no.2
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• pp.225-248
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• 1992

In this paper, word sense disambiguation methods utilizing a knowledge base based on a semantic network are introduced. The basic idea is to keep track of a set of paths in the knowledge base which correspond to the inctemental semantic interpretation of a input sentence. These paths are called the semantic paths. when the parser reads a word, the senses of this word which are not involved in any of the semantic paths are removed. Then the removal operation is propagated through the knowledge base to invoke the removal of the senses of other words that have been read before. This removal operation is called recusively as long as senses can be removed. This is called the recursive word sense removal. Concretion of a vague word's concept is one of the important word sense disambiguation methods. We introduce a method called the path adjustment that extends the conctetion operation. How to use semantic association or syntactic processing in coorporation with the above methods is also considered.