levenshtein-distance

问题 If I have some distance which I do not want to exceed. Example = 2. Do I can break from algoritm before its complete completion knowing the minimum allowable distance? Perhaps there are similar algorithms in which it can be done. It is necessary for me to reduce the time of work programs. 回答1: If you do top-down dynamic programming/recursion + memoization, you could pass the current size as an extra parameter and return early if it exceeds 2. But I think this will be inefficient because you

问题 I want to look up a String in a String[] for the best match of the query. I have heard of Levenshtein Distance. But I cannot determine if I need it or not. Suppose, I have a String query = "Examples" and String[] arrayStr = new String[] {"The Examples String", "The Example String", "Example", "Examples String", "Example String", "Examplestring"}; Now, I want to get the Example from the String[] as the best match. So, Do I need Levenshtein Distance to do it? Alternatively, If someone can point

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 6 years ago . I have two text files which I'd like to compare. What I did is: I've split both of them into sentences. I've measured levenshtein distance between each of the sentences from one file with each of the sentences from second file. I'd like to calculate average similarity between those two text files, however I have

问题 Say I have the following two strings in my database: (1) 'Levi Watkins Learning Center - Alabama State University' (2) 'ETH Library' My software receives free text inputs from a data source, and it should match those free texts to the pre-defined strings in the database (the ones above). For example, if the software gets the string 'Alabama University' , it should recognize that this is more similar to (1) than it is to (2) . At first, I thought of using a well-known string metric like

问题 I am using the Levenshtein distance algorithm to compare a company name provided as a user input against a database of known company names to find closest match. By itself, the algorithm works okay, but I want to build in a Bias so that the edit distance is considered lower if the initial parts of the strings match. For Example, if the search criteria is "ABCD", then both "ABCD Co." and "XYX ABCD" have identical Edit Distance. However I want to add weight to the fact that the initial parts of

问题 I'm trying to come up with the fastest way to make search suggestions. At first I thought a Levenstein UDF function combined with a mysql table would do the job. But using levenshtein, mysql would have to go over every row in the table (tons of words) which would make the query really slow. Now I recently installed and started to use Sphinx (http://sphinxsearch.com/) for fulltext searching mainly because of its performance and tight mysql integration with SphinxSE. So I asked myself if I can

问题 I'm back with another longish question. Having experimented with a number of Python-based Damerau-Levenshtein edit distance implementations, I finally found the one listed below as editdistance_reference() . It seems to deliver correct results and appears to have an efficient implementation. So I set down to convert the code to Cython. on my test data, the reference method manages to deliver results for 11,000 comparisons (for pairs of words aound 12 letters long), while the Cythonized method

问题 I have a dataframe with only one column , and 1000 rows in that column. I need to compare all rows and find Levenshtein distance for all rows . how Do i calculate that ratio or distance in python I have a dataframe as following: #Df StepDescription click confirm button when done you have logged on please log in to proceed click on confirm button Dolb was released successfully Enter your details validate the statement Aval was released sucessfully How to do i Calculate Levenshtein ration for

问题 I create Antiplagiat. I use a shingle method. For example, I have the following shingles: I go to the cinema I go to the cinema1 I go to th cinema Is there a method of calculating the equal hash for these lines? I know of the existence of Levenshtein distance. However, I do not know what I should take source word. Maybe there is a better way than to consider Levenshtein distance. 回答1: The problem with hashing is that, logically, you'll run into 2 strings that differ by a single character that

问题 I use the Levenshtein plugin for MySQL from: http://samjlevy.com/2011/03/MySQL-levenshtein-and-damerau-levenshtein-udfs/ I'm trying a query like: SELECT name FROM database WHERE levenshtein(name, 'testć') the problem is that levenshtein function doesnt handle accented characters. I need levenshtein to recognize characters like "C" and "Ć" (and others accented) as the same. So i decided to replace all of it in MySQL, but cant find any function for that. Like: SELECT name FROM database WHERE