title: Jaro-winkler function: why is the same score matching very similar and very different words?
body: <p>I am using the jaro-winkler fuzzy matching to match names.</p>
  
  <p>I am trying to determine a cut-off range for the similarity score. If the names are too different, I want to exclude them for manual review. </p>
  
  <p>While anything below .4 seemed to be different names entirely, the .4 range seemed fairly similar. </p>
  
  <p>But then I came across strange exceptions, where some names in that range are entirely different, while some names are only one or two letters off(see example below). </p>
  
  <p><em>Can someone explain where there is the wide variation of matching within the same matching score range?</em> </p>
  
  <pre><code>   Estrella     ANNELISE    0.42 
     Arienna      IREANNA     0.43 
     Tayvia       I TAYVIA    0.43
     Amanda       IZABEL      0.44
     Hunter       JOSHUA      0.44
     Ryder        CHARLES     0.45
     Luis         ELIZABETH   0.45 
     Sebastian    JOSE        0.45 
     Christopher  CHISTOPHE   0.46 
     Genayunique  GENAY-UNI   0.46 
     Andreeaonn   ADREEAONN   0.46
     Chistopher   CHRISTOPH   0.46
     Dazharicon   DAZHARION   0.46
     Jennavecia   JENNACVEC   0.46
     Valentiria   VALENTINA   0.46
     Abel         SAMMUEL     0.46
     Dezarea MarieDEZAREA     0.47
     Alexander    ALEXZANDE   0.47
  </code></pre>