Merge branch 'feature/netstandard2' into develop

Author: paulirwin

README.md

@@ -141,7 +141,34 @@ This algorithm is usually used for optical character recognition (OCR) applicati
 
 It can also be used for keyboard typing auto-correction. Here the cost of substituting E and R is lower for example because these are located next to each other on an AZERTY or QWERTY keyboard. Hence the probability that the user mistyped the characters is higher.
 
-<!-- TODO.JB - port Java example code -->
+```cs
+using System;
+using F23.StringSimilarity;
+
+public class Program
+{    
+    public static void Main(string[] args)
+    {
+        var l = new WeightedLevenshtein(new ExampleCharSub());
+
+        Console.WriteLine(l.Distance("String1", "String1"));
+        Console.WriteLine(l.Distance("String1", "Srring1"));
+        Console.WriteLine(l.Distance("String1", "Srring2"));
+    }
+}
+
+private class ExampleCharSub : ICharacterSubstitution
+{
+    public double Cost(char c1, char c2)
+    {
+        // The cost for substituting 't' and 'r' is considered smaller as these 2 are located next to each other on a keyboard
+        if (c1 == 't' && c2 == 'r') return 0.5; 
+
+        // For most cases, the cost of substituting 2 characters is 1.0
+        return 1.0;
+    }
+}
+```
 
 ## Damerau-Levenshtein
 Similar to Levenshtein, Damerau-Levenshtein distance with transposition (also sometimes calls unrestricted Damerau-Levenshtein distance) is the minimum number of operations needed to transform one string into the other, where an operation is defined as an insertion, deletion, or substitution of a single character, or a **transposition of two adjacent characters**.

src/F23.StringSimilarity/F23.StringSimilarity.csproj

@@ -1,9 +1,10 @@
 <Project Sdk="Microsoft.NET.Sdk">
 
   <PropertyGroup>
-    <TargetFramework>netstandard1.0</TargetFramework>
+    <TargetFrameworks>netstandard2.0;net45</TargetFrameworks>
     <PackageId>F23.StringSimilarity</PackageId>
-    <PackageVersion>3.1.0</PackageVersion>
+    <PackageVersion>3.2.0</PackageVersion>
+    <PackageTags>string;similarity;distance;levenshtein;jaro-winkler;lcs;cosine</PackageTags>
     <Title>StringSimilarity.NET</Title>
     <Authors>James Blair, Paul Irwin</Authors>
     <Copyright>Copyright 2018 feature[23]</Copyright>
@@ -17,7 +18,7 @@
   </PropertyGroup>
 
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|AnyCPU'">
-    <DocumentationFile>bin\Release\netstandard1.0\F23.StringSimilarity.xml</DocumentationFile>
+    <DocumentationFile>bin\Release\netstandard2.0\F23.StringSimilarity.xml</DocumentationFile>
   </PropertyGroup>
 
 </Project>

test/F23.StringSimilarity.Tests/F23.StringSimilarity.Tests.csproj

@@ -1,7 +1,7 @@
 <Project Sdk="Microsoft.NET.Sdk">
 
   <PropertyGroup>
-    <TargetFramework>netcoreapp2.0</TargetFramework>
+    <TargetFramework>netcoreapp3.1</TargetFramework>
   </PropertyGroup>
 
   <ItemGroup>