Here is the code (beware because it may be buggy): **************************** Function jaro(By Val str1 As String, By Val str2 As String) As Double Dim l1, l2, lmin, lmax, m, i, j As Integer Dim common As Integer Dim tr As Double Dim a1, a2 As String str1 = clean_string(str1) str2 = clean_string(str2) l1 = Len(str1) l2 = Len(str2) If l1 l2 Then aux = l2 l2 = l1 l1 = aux auxstr = str1 str1 = str2 str2 = auxstr End If lmin = l1 lmax = l2 Dim f1(), f2() As Boolean Re Dim f1(l1), f2(l2) For i = 1 To l1 f1(i) = False Next i For j = 1 To l2 f2(j) = False Next j m = Int((lmax / 2) - 1) common = 0 tr = 0 For i = 1 To l1 a1 = Mid(str1, i, 1) If m lmax Then l = lmax End If For j = f To l a2 = Mid(str2, j, 1) If (a2 = a1) And (f2(j) = False) Then common = common 1 f1(i) = True f2(j) = True Go To linea_exit End If Next j linea_exit: Next i Dim wcd, wrd, wtr As Double l = 1 For i = 1 To l1 If f1(i) Then For j = l To l2 If f2(j) Then l = j 1 a1 = Mid(str1, i, 1) a2 = Mid(str2, j, 1) If a1 CORP.Example: Function clean_string(str1 As String) As String str1 = Replace(str1, ".", "") str1 = Replace(str1, ",", "") str1 = Replace(str1, "-", "") str1 = Replace(str1, ";", "") str1 = Replace(str1, ":", "") str1 = Replace(str1, "", "A") str1 = Replace(str1, "", "E") str1 = Replace(str1, "", "I") str1 = Replace(str1, "", "O") str1 = Replace(str1, "", "U") str1 = Replace(str1, " COMPANY ", " CO ") str1 = Replace(str1, " CORPORATION ", " CO ") ....Sign up today to browse the FREE personal ads of available Iloilo City singles, and hook up online using our completely free Jaro Iloilo online dating service! Jaro Iloilo Chat Rooms | Jaro Iloilo Men | Jaro Iloilo Women | Jaro Iloilo Christian Dating | Jaro Iloilo Black Singles Jaro Iloilo Latin Singles | Jaro Iloilo Mature Singles | Jaro Iloilo Cougars | Jaro Iloilo BBW | Jaro Iloilo Singles knowing someone is good to start friendship but if your not interested don't waste your time chatting with nonsense.
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Thanks, Thomas Jaro Winkler algorithm is an improved version of the Edit Distance algorithm much the same thing but with an example an understanding of Jaro n' his mate Winklers Algorithm
as for the paper I haven't seen any that explain the algorithm Hi Thomas, A couple of month ago I've studied different kinds of approximate string matching algorithms, among them Jaro-Winkler.
Although often referred to as a distance metric, the Jaro–Winkler distance is not a metric in the mathematical sense of that term because it does not obey the triangle inequality. The number of matching (but different sequence order) characters divided by 2 defines the number of transpositions.
For example, in comparing CRATE with TRACE, only 'R' 'A' 'E' are the matching characters, i.e. Although 'C', 'T' appear in both strings, they are farther than 1, i.e., floor(5/2)-1=1. In Dw Ay NE versus Du ANE the matching letters are already in the same order D-A-N-E, so no transpositions are needed.
Compute the (partial) similarity between strings values.
This method initialises the similarity measurement between string values.
I've developed an VBAccess code to test them prior to developing the ABAP final application.
Basically, it computes what i've understood of the papers you mentioned...
The similarity algorithms are ‘step’, ‘linear’, ‘exp’, ‘gauss’ or ‘squared’.
In computer science and statistics, the Jaro–Winkler distance is a string metric for measuring the edit distance between two sequences. Winkler of the Jaro distance metric (1989, Matthew A. Informally, the Jaro distance between two words is the minimum number of single-character transpositions required to change one word into the other. The lower the Jaro–Winkler distance for two strings is, the more similar the strings are.
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