(PHP 4, PHP 5, PHP 7, PHP 8)
similar_text — İki dizge arasındaki benzerliği hesaplar
Programming Classics: Implementing the World's Best Algorithms by Oliver (ISBN 0-131-00413-1) kitabında açıkladığı şekilde iki dizge arasındaki benzerliği hesaplar. Ancak bu gerçeklenim Oliver'in kod örneğindeki gibi bir yığıt kullanmaz. Ayrıca bu algoritmanın hesaplama karmaşıklığı, N en uzun dizgenin uzunluğu olmak üzere O(N**3)'tür.
dizge1İlk dizge.
dizge2İkinci dizge.
Bilginize:
dizge1vedizge2yer değiştirise farklı sonuçlar ortaya çıkabilir; aşağıdaki örnek fikir verebilir.
yüzdeBenzerlik oranını belirtmek için kullanılır. Bir gönderimi üçüncü bağımsız değişkende aktararak, similar_text() işlevinin sonucu verilen dizgelerin uzunluklarının ortalamasının 100 katına bölünerek benzerlik yüzde olarak hesaplanır.
Her iki dizgede eşleşen karakterlerin sayısı döner.
Eşleşen karakterlerin sayısı, en uzun ilk ortak alt dizgeyi bularak ve bunu önekler ve son ekler için ard arda bularak hesaplanır. Bulunan tüm ortak alt dizelerin uzunlukları toplanır.
Örnek 1 - similar_text() bağımsız değişken takaslama örneği
dizge1 ve dizge2
takaslandığında farklı sonuçlar elde edileceğini gösteren örnek.
<?php
$sim = similar_text('bafoobar', 'barfoo', $perc);
echo "similarity: $sim ($perc %)\n";
$sim = similar_text('barfoo', 'bafoobar', $perc);
echo "similarity: $sim ($perc %)\n";Yukarıdaki örnek şuna benzer bir çıktı üretir:
similarity: 5 (71.428571428571 %) similarity: 3 (42.857142857143 %)
Hey there,
Be aware when using this function, that the order of passing the strings is very important if you want to calculate the percentage of similarity, in fact, altering the variables will give a very different result, example :
<?php
$var_1 = 'PHP IS GREAT';
$var_2 = 'WITH MYSQL';
similar_text($var_1, $var_2, $percent);
echo $percent;
// 27.272727272727
similar_text($var_2, $var_1, $percent);
echo $percent;
// 18.181818181818
?>Please note that this function calculates a similarity of 0 (zero) for two empty strings.
<?php
similar_text("", "", $sim);
echo $sim; // "0"
?>Actually similar_text() is not bad...
it works good. But before processing i think is a good way to make a little mod like this
$var_1 = strtoupper("doggy");
$var_2 = strtoupper("Dog");
similar_text($var_1, $var_2, $percent);
echo $percent; // output is 75 but without strtoupper output is 50Note that this function is case sensitive:
<?php
$var1 = 'Hello';
$var2 = 'Hello';
$var3 = 'hello';
echo similar_text($var1, $var2); // 5
echo similar_text($var1, $var3); // 4Recursive algorithm usually is very elegant one. I found a way to get better precision without the recursion. Imagine two different (or same) length ribbons with letters on each. You simply shifting one ribbon to left till it matches the letter the first.
<?php
function similarity($str1, $str2) {
$len1 = strlen($str1);
$len2 = strlen($str2);
$max = max($len1, $len2);
$similarity = $i = $j = 0;
while (($i < $len1) && isset($str2[$j])) {
if ($str1[$i] == $str2[$j]) {
$similarity++;
$i++;
$j++;
} elseif ($len1 < $len2) {
$len1++;
$j++;
} elseif ($len1 > $len2) {
$i++;
$len1--;
} else {
$i++;
$j++;
}
}
return round($similarity / $max, 2);
}
$str1 = '12345678901234567890';
$str2 = '12345678991234567890';
echo 'Similarity: ' . (similarity($str1, $str2) * 100) . '%';
?>To calculate the percentage of similarity between two strings without depending on the order of the parameters and be case insensitive, I use this function based on levenshtein's distance:
<?php
// string similarity calculated using levenshtein
static function similarity($a, $b)
{
return 1 - (levenshtein(strtoupper($a), strtoupper($b)) / max(strlen($a), strlen($b)));
}
?>
This will always return a number between 0 and 1, representing the percentage, for instance 0.8 represents 80% similar strings.
If you want this to be case-sensitive, just remove the strtoupper() functions.If performance is an issue, you may wish to use the levenshtein() function instead, which has a considerably better complexity of O(str1 * str2).The speed issues for similar_text seem to be only an issue for long sections of text (>20000 chars).
I found a huge performance improvement in my application by just testing if the string to be tested was less than 20000 chars before calling similar_text.
20000+ took 3-5 secs to process, anything else (10000 and below) took a fraction of a second.
Fortunately for me, there was only a handful of instances with >20000 chars which I couldn't get a comparison % for.If you have reserved names in a database that you don't want others to use, i find this to work pretty good.
I added strtoupper to the variables to validate typing only. Taking case into consideration will decrease similarity.
<?php
$query = mysql_query("select * from $table") or die("Query failed");
while ($row = mysql_fetch_array($query)) {
similar_text(strtoupper($_POST['name']), strtoupper($row['reserved']), $similarity_pst);
if (number_format($similarity_pst, 0) > 90){
$too_similar = $row['reserved'];
print "The name you entered is too similar the reserved name "".$row['reserved'].""";
break;
}
}
?>Well, as mentioned above the speed is O(N^3), i've done a longest common subsequence way that is O(m.n) where m and n are the length of str1 and str2, the result is a percentage and it seems to be exactly the same as similar_text percentage but with better performance... here's the 3 functions i'm using..
<?php
function LCS_Length($s1, $s2)
{
$m = strlen($s1);
$n = strlen($s2);
//this table will be used to compute the LCS-Length, only 128 chars per string are considered
$LCS_Length_Table = array(array(128),array(128));
//reset the 2 cols in the table
for($i=1; $i < $m; $i++) $LCS_Length_Table[$i][0]=0;
for($j=0; $j < $n; $j++) $LCS_Length_Table[0][$j]=0;
for ($i=1; $i <= $m; $i++) {
for ($j=1; $j <= $n; $j++) {
if ($s1[$i-1]==$s2[$j-1])
$LCS_Length_Table[$i][$j] = $LCS_Length_Table[$i-1][$j-1] + 1;
else if ($LCS_Length_Table[$i-1][$j] >= $LCS_Length_Table[$i][$j-1])
$LCS_Length_Table[$i][$j] = $LCS_Length_Table[$i-1][$j];
else
$LCS_Length_Table[$i][$j] = $LCS_Length_Table[$i][$j-1];
}
}
return $LCS_Length_Table[$m][$n];
}
function str_lcsfix($s)
{
$s = str_replace(" ","",$s);
$s = ereg_replace("[��������]","e", $s);
$s = ereg_replace("[������������]","a", $s);
$s = ereg_replace("[��������]","i", $s);
$s = ereg_replace("[���������]","o", $s);
$s = ereg_replace("[��������]","u", $s);
$s = ereg_replace("[�]","c", $s);
return $s;
}
function get_lcs($s1, $s2)
{
//ok, now replace all spaces with nothing
$s1 = strtolower(str_lcsfix($s1));
$s2 = strtolower(str_lcsfix($s2));
$lcs = LCS_Length($s1,$s2); //longest common sub sequence
$ms = (strlen($s1) + strlen($s2)) / 2;
return (($lcs*100)/$ms);
}
?>
you can skip calling str_lcsfix if you don't worry about accentuated characters and things like that or you can add up to it or modify it for faster performance, i think ereg is not the fastest way?
hope this helps.
Georges