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copied!<p>I can't think of any situation in which this would be really useful. Even if I could, I suspect the added CPU cycles needed to sort fuzzy values would be more than those "extra comparisons" you allude to. But I'll still offer a suggestion.</p> <p>Consider this possibility (all strings use the 27 characters a-z and _):</p> <pre><code> 11111111112 12345678901234567890 1/ now_is_the_time 2/ now_is_never 3/ now_we_have_to_go 4/ aaa 5/ ___ </code></pre> <p>Obviously strings 1 and 2 are more similar that 1 and 3 and <em>much</em> more similar than 1 and 4.</p> <p>One approach is to scale the difference value for each identical character position and use the first different character to set the last position.</p> <p>Putting aside signs for the moment, comparing string 1 with 2, the differ in position 8 by 'n' - 't'. That's a difference of 6. In order to turn that into a single digit 1-9, we use the formula:</p> <pre><code>digit = ceiling(9 * abs(diff) / 27) </code></pre> <p>since the maximum difference is 26. The minimum difference of 1 becomes the digit 1. The maximum difference of 26 becomes the digit 9. Our difference of 6 becomes 3.</p> <p>And because the difference is in position 8, out comparison function will return 3x10<sup>-8</sup> (actually it will return the negative of that since string 1 comes <em>after</em> string 2.</p> <p>Using a similar process for strings 1 and 4, the comparison function returns -5x10<sup>-1</sup>. The highest possible return (strings 4 and 5) has a difference in position 1 of '-' - 'a' (26) which generates the digit 9 and hence gives us 9x10<sup>-1</sup>.</p> <p>Take these suggestions and use them as you see fit. I'd be interested in knowing how your fuzzy comparison code ends up working out.</p>

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