CAJ | 학술논문

针对Jaro-Winkler算法在计算两个字符串的相似度时只考虑字符的换位数目，未考虑字符插入和删除编辑操作的问题，提出一种基于Levenshtein算法改进Jaro-Winkler算法的方法。通过改进相似度的计算公式和调整关联系数pd，实现Jaro-Winkler算法的改进，提高字符串匹配的准确度。基于内容丰富的本地文本数据库，将改进Jaro-Winkler算法应用于迎宾机器人语音交互中的字符串匹配，其正确率大于96%。测试结果表明，迎宾机器人能够语音交互更多的内容和快速地应答提问，并实现特定的迎宾动作。
침대Jaro-Winkler산법재계산량개자부천적상사도시지고필자부적환위수목，미고필자부삽입화산제편집조작적문제，제출일충기우Levenshtein산법개진Jaro-Winkler산법적방법。통과개진상사도적계산공식화조정관련계수pd，실현Jaro-Winkler산법적개진，제고자부천필배적준학도。기우내용봉부적본지문본수거고，장개진Jaro-Winkler산법응용우영빈궤기인어음교호중적자부천필배，기정학솔대우96%。측시결과표명，영빈궤기인능구어음교호경다적내용화쾌속지응답제문，병실현특정적영빈동작。
When measuring the similarity of two strings, Jaro-Winkler distance only considers the number of transpositions, without considering the insertions and deletions. Aiming at this problem, proposes an improved Jaro-Winkler distance method based on the Levenshtein distance. Modifies the formula of similarity and adjusting the correlation coefficient of pd to improve Jaro-Winkler distance, and the accuracy of the strings matching is increased. Based on the local database with a large number of text strings, applies the improved Jaro-Winkler distance to achieve the strings matching in speech interaction of reception robot, and its accuracy is higher than 96%. Test results show that reception robot can realize more words and quickly reply to questions by speech interaction with specific welcome actions.