word_freq($t2,$sample) ? $analyser[0]++ : $analyser[1]++; word_freq($t1,$sample) > word_freq($t2,$sample) ? $analyser2[0]++ : $analyser2[1]++; for($i = 2; $i <= $num_funcs; $i++){ calculate_point ($stats[0][$i], $stats[1][$i], $stats[2][$i], $analyser); calculate_point2($stats[0][$i], $stats[1][$i], $stats[2][$i], $analyser2); } ?> TEXT ANALYSER - Turing

TURING - Text Universal Recognition In Natural Gateways

This was done as a school assignment (Applied Artificial Intelligence at Blekinge Institute of Technology).

The idea is to load two texts and save the characteristics. You then provide a sample from one of the texts. I then should be able to decide from which one of the two text your sample comes from.

Training set 1 | Training set 2 | Sample

Behind the scenes (Technical details) "; foreach($stats[$i] as $value) echo ""; echo ""; }?>
Text Word count Name Word length Sentence length Commas Newlines Similiarity Semicolons words/ line Quote length Colons Words t1 Words t2
$value
CLICK TO VIEW THE RESULT

Algorithm 1: One point for the closest match.
Algorithm 2: The assigned score is the ratio between the difference of the closest and not.

In favor of text " . ($i+1) . ": " . rounding($analyser[$i]) . " -------- " . rounding($analyser2[$i]) . ""; ?>