public string FindBuilding(string building, string city, string street)
{
string commandText = @"select distinct building from hot_water where city=@c and street=@s";
Dictionary <string, string> parameters = new Dictionary <string, string>
{
{ "c", city },
{ "s", street }
};
var fetchedData = FetchData(commandText, parameters).Select(t => t[0]).ToArray();
double minMatch = 99;
double match;
string matchedString = "";
foreach (var e in fetchedData)
{
match = ComparisonMetrics.JaccardDistance(e, building);
if (match < minMatch)
{
minMatch = match;
matchedString = e;
}
}
if (minMatch == 99)
{
return(null);
}
return(matchedString);
}
public void WhenMatchingStrings_ShouldReturnExpectedValue(double pValue, double expectedValue)
{
const string kevin = "kevin";
var result = ComparisonMetrics.JaroWinklerDistanceWithPrefixScale(kevin, kevin, pValue);
Assert.Equal(expectedValue, result);
}
public void WhenDifferentStrings_ShouldReturnExpectedValue(double pValue, double expectedValue)
{
const string kevin = "kevin";
const string abcxyz123 = "abcxyz123";
var result = ComparisonMetrics.JaroWinklerDistanceWithPrefixScale(kevin, abcxyz123, pValue);
Assert.Equal(expectedValue, result);
}
private async Task <BsonDocument> FindApproximateProduct(string name)
{
var revCollection = _database.GetCollection <BsonDocument>("reviews");
using (var cursor = await revCollection.FindAsync(new BsonDocument()))
{
while (await cursor.MoveNextAsync())
{
foreach (var document in cursor.Current)
{
if (ComparisonMetrics.ApproximatelyEquals(document["name"].AsString, name, new[] { FuzzyStringComparisonOptions.UseLevenshteinDistance }.ToList(), FuzzyStringComparisonTolerance.SuperStrong))
{
return(document);
}
}
}
}
return(null);
}
