/**
* This method applies the Winnowing Algorithmn described at the article
* `Winnowing: Local Algorithms for Document Fingerprinting` by Saul Schleimer,
* Daniel S. Wilkerson, and Alex Aiken. It consists in extracting the smallest hash
* in a window of characters taken directly from the text. This way it's possible to
* identify similarities across documents since you can have different individual hashs
* in a very similar sequence of hashs. For more information read the article.
*
* @public
* @param $documentContent the document text
* @return {array} an array of Fingerprints
*/
public function extractFingerprint($documentContent)
{
$fingerprints = array();
$contentLength = strlen($documentContent);
$hashCount = $contentLength - $this->k;
$windowSize = $this->threshold - $this->k + 1;
for ($i = 0; $i < $hashCount; $i++) {
$window = array();
for ($j = $i; $j < $i + $windowSize; $j++) {
$value = substr($documentContent, $j, $this->k);
$window[$j] = hash('md5', $value, false);
}
reset($window);
$min = key($window);
$fingerprint = $window[$min];
foreach ($window as $index => $hash) {
if ($hash <= $fingerprint) {
$min = $index;
$fingerprint = $hash;
}
}
$fingerprints[$min] = $fingerprint;
}
$ret = array();
$normalizedLocation = 0;
foreach ($fingerprints as $loc => $hash) {
array_push($ret, Fingerprint::fill($hash, $loc, $normalizedLocation++));
}
return $ret;
}
