Solution Algorithm of String Similarity Based on Improved Levenshtein Distance
Jiang Hu · Jisuanji gongcheng · 2014
When calculating the similarity of strings, the Levenshtein Distance(LD) algorithm only considers the operating times and ignores the common substrings of two strings. Aiming at this problem, an improved Levenshtein distance algorithm is proposed to calculate the similarity. The new algorithm improves the formula of similarity and the Levenshtein matrix. When calculating the distance, the new algorithm calculates the longest common substring and all the LD backtracking paths in the original matrix at the same time. Selecting a word in the experiment as a source string, a set of similar words of the different degrees of the source string as a target string, the new similarity measure formula is compared with the existing string similarity calculation method, the new formula reduces the number of target strings into the winner table with similarity sample range and standard deviation of 0.331 and 0.150, respectively. Experimental results show that the new algorithm has higher accuracy and more flexible searching way in the same space complexity.