论文标题
在韩国聊天机器人中进行错误的句子分类的集成eojeol嵌入
Integrated Eojeol Embedding for Erroneous Sentence Classification in Korean Chatbots
论文作者
论文摘要
本文试图分析聊天机器人的韩国句子分类系统。句子分类是根据预定义类别对输入句子进行分类的任务。但是，输入句子中包含的拼写或空间错误会导致形态分析和令牌化中的问题。本文提出了一种嵌入的综合eojeol（韩国句法单词）的新方法，以减少分析不良的词素可能对句子分类产生的效果。它还提出了两种噪声插入方法，以进一步提高分类性能。我们的评估结果表明，所提出的系统比基线系统更准确地分类了错误的句子。
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
