72 lines
1.9 KiB
C#
72 lines
1.9 KiB
C#
using System;
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using System.Collections.Generic;
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using System.Linq;
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using System.Text;
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using System.Threading.Tasks;
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namespace BlubbFish.Iot.Snips.Helper {
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public class Texthelper {
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public static Int32 ComputeLevenshteinDistance(String source, String target) {
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if((source == null) || (target == null)) {
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return 0;
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}
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if((source.Length == 0) || (target.Length == 0)) {
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return 0;
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}
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if(source == target) {
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return source.Length;
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}
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Int32 sourceWordCount = source.Length;
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Int32 targetWordCount = target.Length;
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// Step 1
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if(sourceWordCount == 0) {
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return targetWordCount;
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}
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if(targetWordCount == 0) {
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return sourceWordCount;
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}
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Int32[,] distance = new Int32[sourceWordCount + 1, targetWordCount + 1];
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// Step 2
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for(Int32 i = 0; i <= sourceWordCount; distance[i, 0] = i++) { }
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for(Int32 j = 0; j <= targetWordCount; distance[0, j] = j++) { }
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for(Int32 i = 1; i <= sourceWordCount; i++) {
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for(Int32 j = 1; j <= targetWordCount; j++) {
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// Step 3
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Int32 cost = (target[j - 1] == source[i - 1]) ? 0 : 1;
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// Step 4
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distance[i, j] = Math.Min(Math.Min(distance[i - 1, j] + 1, distance[i, j - 1] + 1), distance[i - 1, j - 1] + cost);
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}
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}
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return distance[sourceWordCount, targetWordCount];
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}
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public static Double CalculateSimilarity(String source, String target) {
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if((source == null) || (target == null)) {
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return 0.0;
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}
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if((source.Length == 0) || (target.Length == 0)) {
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return 0.0;
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}
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if(source == target) {
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return 1.0;
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}
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Int32 stepsToSame = ComputeLevenshteinDistance(source, target);
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return (1.0 - (stepsToSame / (Double)Math.Max(source.Length, target.Length)));
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}
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}
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}
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