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      Integrated Eojeol Embedding for Erroneous Sentence Classification in Korean Chatbots

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          Abstract

          This paper attempts to analyze the Korean sentence classification system for a chatbot. Sentence classification is the task of classifying an input sentence based on predefined categories. However, spelling or space error contained in the input sentence causes problems in morphological analysis and tokenization. This paper proposes a novel approach of Integrated Eojeol (Korean syntactic word separated by space) Embedding to reduce the effect that poorly analyzed morphemes may make on sentence classification. It also proposes two noise insertion methods that further improve classification performance. Our evaluation results indicate that the proposed system classifies erroneous sentences more accurately than the baseline system by 17%p.0

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          Author and article information

          Journal
          12 April 2020
          Article
          2004.05744

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          9 pages, 2 figures
          cs.CL

          Theoretical computer science

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