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ISSN : 1226-9654
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속성적 관점에 기반한단어 재인시의 의미 처리 가능성 연구: 연결주의 모델링
Semantic Process Possibility Research in Featural View: Connectionist Modeling
남기춘 (고려대학교)
남호성 (고려대학교)
초록
단어의 의미처리는 개별 단어가 나타내는 개념(concept)들 간의 의미적 관련성을 효과적으로 표상할 수 있어야 한다. 본 연구는 의미 처리의 모델로서, 속성적 관점에 기반한 연결주의 모델을 제시하고, 단어와 의미 간의 관계를 학습하였다. 학습 과정 이후 모델용의 어휘 판단 과제를 수행하여, 종래 행동실험에서 의미 처리와 관련되어 나타나는 것으로 언급되었던 효과들이 제대로 모사되었는가 통계적으로 검증하였다. 모델링 수행 결과, 모델은 빈도효과(frequency effect), 단어 유사성 효과(word similarity effect), 의미 충실도 효과(semantic richness effect)와 의미 점화 효과(semantic priming effect)를 정상적으로 모사하는데 성공함으로써, 모델이 정상적인 의미의 학습 및 처리가 가능함을 보였다. 본 연구의 결과는, 속성적 관점 기반의 의미 표상(representation) 구조가 충분히 실제 사람의 언어처리를 반영할 가능성을 제시한다.
- keywords
- 개념 표상, 의미 처리, 속성적 관점, 연결주의 모델링, conceptual representation, semantic process, featural view, connectionist modeling
Abstract
Semantic processing should effectively encode the meaning of a word and represent semantic relationship among individual words. This study proposed a connectionist model employing features as basic units for semantic processing among words and learning the relationship between the words and the associated meanings. The model statistically proved the capability to effectively simulate behavioral results from lexical decision tasks. In addition, the model successfully simulated the frequency effect, the word similarity effect, the semantic richness effect, and the semantic priming effect, which have been observed in behavioral studies. These results suggest that features are possibly basic units for human’s semantic processing.
- keywords
- 개념 표상, 의미 처리, 속성적 관점, 연결주의 모델링, conceptual representation, semantic process, featural view, connectionist modeling
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