This minimum number of changes is called the edit distance.
最小数量的更改称为编辑距离。
In fact, a Levenshtein distance is also known as an edit distance.
实际上，Levenshtein距离也称作编辑距离。
Design an algorithm to calculate any two of the string edit distance.
设计一个算法，计算任意两个字符串的编辑距离。
Sort: Sort the words by edit distance, keeping words found at each step together.
排序：按照编辑距离排序单词，把每一步骤中找到的单词放在一起。
The edit distance used in Jazzy differs from the Levenshtein distance defined earlier.
在Jazzy 中使用的编辑距离与以前在 Levenshtein 距离中的定义不同。
This paper reviews some formulas for event sequence similarity calculation, and proposes an improved edit distance.
分析了事件序列相似性的计算公式，提出了改进的编辑距离公式。
The strength of the Aspell algorithm is the way it USES edit distance at both the word level and the phonetic code level.
Aspell算法的优势在于它利用编辑距离的方式，它在单词级别上和语音代码级别上都使用编辑距离。
Compared to the 0-1 polynomial kernel, our newly designed string kernel based on edit distance can effectively measure the similarity between sequences.
相比先前基于0 - 1编码的多项式核，采用新的字符串核能较好地度量序列之间的相似度。
Lucene supports fuzzy searches based on the Levenshtein Distance, or Edit Distance algorithm. To do a fuzzy search use the tilde, "~", symbol at the end of a Single word Term.
Lucene支持基于编辑距离算法的模糊搜索，你可以使用波浪符号“~”放在查询词的后面，比如搜索一个与“roam”拼写相近的词可以使用。
For these codes, add all dictionary words that have the same phonetic code as the misspelled word and whose edit distance from the misspelled word is less than a given threshold.
对于这些代码，加入字典中所有与拼写错误单词语音编码相同的单词，以及与拼写错误单词的编辑距离小于指定阈值的单词。
Next we used distributional similarity as a feature in the discriminative maximum entropy model, with edit distance, phonetic similarity, and language model as other features.
我们还将分布式相似度作为一个特征用于最大熵判别模型中，结合编辑距离、发音相似度、语言模型等基本特征。
Best guess: If no Suggestions have been found, add all dictionary words that have the same phonetic code as the misspelled word and with the smallest edit distance from the misspelled word.
最佳猜测：如果没有找到建议，就加入字典中所有与拼写错误的单词的语音代码相同的单词，以及与拼写错误的单词编辑距离最小的单词。
Based on the requirement of data processing, after analyzing the existing algorithm of Levenshtein Distance, the number of edit operation was decreased by extending the transposition operation.
基于数据处理的需要，在分析原有编辑距离算法的基础上，通过拓展交换操作减少编辑操作的数量。
The approach of improved edit-distance has more advantages than original edit-distance algorithm, such as easily extending, high precision and so on. It has gotten a satisfying result.
改进编辑距离的算法与单纯基于语义辞典计算句子相似度的算法相比，具有便于扩展，准确率高等优点，在英文辅助写作领域取得了令人满意的效果。
The approach of improved edit-distance has more advantages than original edit-distance algorithm, such as easily extending, high precision and so on. It has gotten a satisfying result.
改进编辑距离的算法与单纯基于语义辞典计算句子相似度的算法相比，具有便于扩展，准确率高等优点，在英文辅助写作领域取得了令人满意的效果。
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