The Jaro distance is a measure of edit distance between two strings; its inverse, called the Jaro similarity, is a measure of two strings' similarity: the higher the value, the more similar the strings are. The score is normalized such that   0   equates to no similarities and   1   is an exact match.



Definition
The Jaro similarity   




d

j




{\displaystyle d_{j}}

   of two given strings   




s

1




{\displaystyle s_{1}}

   and   




s

2




{\displaystyle s_{2}}

   is

 




d

j


=

{




0



if 

m
=
0






1
3



(


m


|


s

1



|




+


m


|


s

2



|




+



m
−
t

m


)




otherwise









{\displaystyle d_{j}=\left\{{\begin{array}{l l}0&{\text{if }}m=0\\{\frac {1}{3}}\left({\frac {m}{|s_{1}|}}+{\frac {m}{|s_{2}|}}+{\frac {m-t}{m}}\right)&{\text{otherwise}}\end{array}}\right.}


Where:

 



m


{\displaystyle m}

   is the number of matching characters;
 



t


{\displaystyle t}

   is half the number of transpositions.


Two characters from   




s

1




{\displaystyle s_{1}}

   and   




s

2




{\displaystyle s_{2}}

   respectively, are considered matching only if they are the same and not farther apart than   




⌊



max
(

|


s

1



|

,

|


s

2



|

)

2


⌋

−
1


{\displaystyle \left\lfloor {\frac {\max(|s_{1}|,|s_{2}|)}{2}}\right\rfloor -1}

 characters.

Each character of   




s

1




{\displaystyle s_{1}}

   is compared with all its matching characters in   




s

2




{\displaystyle s_{2}}

. Each difference in position is half a transposition; that is, the number of transpositions is half the number of characters which are common to the two strings but occupy different positions in each one.



Example
Given the strings   




s

1




{\displaystyle s_{1}}

   DWAYNE   and   




s

2




{\displaystyle s_{2}}

   DUANE   we find:

 



m
=
4


{\displaystyle m=4}


 




|


s

1



|

=
6


{\displaystyle |s_{1}|=6}


 




|


s

2



|

=
5


{\displaystyle |s_{2}|=5}


 



t
=
0


{\displaystyle t=0}




We find a Jaro score of:

 




d

j


=


1
3



(


4
6


+


4
5


+



4
−
0

4


)

=
0.822


{\displaystyle d_{j}={\frac {1}{3}}\left({\frac {4}{6}}+{\frac {4}{5}}+{\frac {4-0}{4}}\right)=0.822}




Task
Implement the Jaro algorithm and show the similarity scores for each of the following pairs:

 ("MARTHA", "MARHTA")
 ("DIXON", "DICKSONX")
 ("JELLYFISH", "SMELLYFISH")


 See also
 Jaro–Winkler distance on Wikipedia.


ClearAll[JaroDistance]
JaroDistance[s_String, t_String] := Module[{slen, tlen, maxdistance, smatches, tmatches, matches, transpositions, start, end, k, schar, tchar},
  slen = StringLength[s];
  tlen = StringLength[t];
  schar = Characters[s];
  tchar = Characters[t];
  If[slen == tlen == 0,
   1
   ,
   maxdistance = Floor[Max[slen, tlen]/2] - 1;
   smatches = ConstantArray[False, slen];
   tmatches = ConstantArray[False, tlen];
   matches = transpositions = 0;
   Do[
    start = Max[0, i - maxdistance];
    end = Min[i + maxdistance + 1, tlen];
    start = Max[1, i - maxdistance];
    end = Min[i + maxdistance + 1, tlen];
 
    Do[
     If[! tmatches[[j]],
      If[schar[[i]] == tchar[[j]],
       smatches[[i]] = True;
       tmatches[[j]] = True;
       matches++;
       Break[];
       ]
      ]
     ,
     {j, start, end}
     ]
    ,
    {i, slen}
    ];
   If[matches == 0,
    0
    ,
    k = 1;
    Do[
     If[smatches[[i]],
      While[! tmatches[[k]],
       k++;
       ];
      If[schar[[i]] != tchar[[k]],
       transpositions++;
       ];
      k++;
      ]
     ,
     {i, slen}
     ];
    N@(matches/slen + matches/tlen + (matches - transpositions/2)/matches)/3
    ]
   ]
  ]
JaroDistance["DWAYNE", "DUANE"]
JaroDistance["MARTHA", "MARHTA"]
JaroDistance["DIXON", "DICKSONX"]
JaroDistance["JELLYFISH", "SMELLYFISH"]