JacekSzybisz.FuzzyMatch 1.0.0

Library is used to perform fuzzy matching (matching simillar strings). It uses Levenshtein Distance algorithms to perform this operation.

In information theory, linguistics and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. Informally, the Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other. It is named after the Soviet mathematician Vladimir Levenshtein, who considered this distance in 1965.[1]
https://en.wikipedia.org/wiki/Levenshtein_distance

Levenshtein distance may also be referred to as edit distance, although that term may also denote a larger family of distance metrics.[2]:32 It is closely related to pairwise string alignments.

Install-Package JacekSzybisz.FuzzyMatch -Version 1.0.0
dotnet add package JacekSzybisz.FuzzyMatch --version 1.0.0
<PackageReference Include="JacekSzybisz.FuzzyMatch" Version="1.0.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add JacekSzybisz.FuzzyMatch --version 1.0.0
The NuGet Team does not provide support for this client. Please contact its maintainers for support.

Fuzzy Match

Library is used to perform fuzzy matching (matching simillar strings ). It uses Levenshtein Distance algorithms to perform this operation. User can specify sensitive of algorithm using maxDistance parameter.

Levenshtein Distance

In information theory, linguistics and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. Informally, the Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other. It is named after the Soviet mathematician Vladimir Levenshtein, who considered this distance in 1965.[1]
https://en.wikipedia.org/wiki/Levenshtein_distance

Usage
using System;
using JacekSzybisz.FuzzyMatch;
using JacekSzybisz.FuzzyMatch.Algorithms.LevenshteinDistance;

namespace FuzzyMatch.Sample
{
    class Program
    {
        static void Main(string[] args)
        {
            IFuzzyMatchProvider fuzzyMatchProvider = new FuzzyMatchProvider(new LevenshteinDistanceService());
     
            var isMatch = fuzzyMatchProvider.IsMatch("Honda", "Hyundai", 2);
            if (isMatch)
            {
                Console.WriteLine("Honda and Hyundai is similar enough to be considered as match");
            }
        }
    }
}


Fuzzy Match

Library is used to perform fuzzy matching (matching simillar strings ). It uses Levenshtein Distance algorithms to perform this operation. User can specify sensitive of algorithm using maxDistance parameter.

Levenshtein Distance

In information theory, linguistics and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. Informally, the Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other. It is named after the Soviet mathematician Vladimir Levenshtein, who considered this distance in 1965.[1]
https://en.wikipedia.org/wiki/Levenshtein_distance

Usage
using System;
using JacekSzybisz.FuzzyMatch;
using JacekSzybisz.FuzzyMatch.Algorithms.LevenshteinDistance;

namespace FuzzyMatch.Sample
{
    class Program
    {
        static void Main(string[] args)
        {
            IFuzzyMatchProvider fuzzyMatchProvider = new FuzzyMatchProvider(new LevenshteinDistanceService());
     
            var isMatch = fuzzyMatchProvider.IsMatch("Honda", "Hyundai", 2);
            if (isMatch)
            {
                Console.WriteLine("Honda and Hyundai is similar enough to be considered as match");
            }
        }
    }
}


Release Notes

Initial version

  • .NETStandard 2.0

    • No dependencies.

This package is not used by any popular GitHub repositories.

Version History

Version Downloads Last updated
1.0.0 178 9/13/2018