NAME

SYNOPSIS

  my $text = "A do run run run, a do run run";
  my $kgram = Algorithm::RabinKarp->new($window, $text);

or

  my $kgram2 = Algorithm::RabinKarp->new($window, $fh);

or my $kgram3 = Algorithm::RabinKarp->new($window, sub { ... return $num, $position; });

  my ($hash, $start_position, $end_position) = $kgram->next;
  
  my @values = $kgram->values;
  
  my %occurances; # a dictionary of all kgrams.
  while (my ($hash, @pos) = @{shift @values}) {
    push @{$occurances{$hash}}, \@pos; 
  }
  
  my $needle = Algorithm::RabinKarp->new(6, "needle");
  open my $fh, '<', "haystack.txt";
  my $haystack = Algorithm::RabinKarp->new(6, $fh);
  my $needle_hash = $needle->next;
  
  while (my ($hay_hash, @pos) = $haystack->next) {
    warn "Possible match for 'needle' at @pos" 
      if $needle_hash eq $hay_hash;
  }

DESCRIPTION

  $H[ $c[2..$k + 1] ] = (( $H[ $c[1..$k] ] - $c[1] ** $k ) + $c[$k+1] ) * $k

The results of this hash encodes information about the next k values in the stream (hense k-gram.) This means for any given stream of length n integer values (or characters), you will get back n - k + 1 hash values.

For best results, you will want to create a code generator that filters your data to remove all unnecessary information. For example, in a large english document, you should probably remove all white space, as well as removing all capitalization.

INTENT

Schleimer, Wilkerson, and Aiken suggest preproccessing to remove unnecessary information (like whitespace), as well as known redundent information (like, say, copyright notices or other boilerplate that is 'acceptable'.)

They also suggest a post processing pass to reduce data volume, using a technique called winnowing (see the link at the end of this documentation.)

METHODS

new($k, [FileHandle|Scalar|Coderef] )

Creates a new hash generator. If you provide a callback function, it must return the next integer value in the stream. Additionally, you may return the original position of the value in the stream (ie, you may have been filtering characters out because they're redundant.)

next()

Returns an array containing (kgram hash value, start position , end position, start, end) for every call that can have a hash generated, or () when we have reached the end of the stream.

"next()" pulls the first $k from the stream on the first call. Each successive call to "next()" has a complexity of O(1).

values

Returns an array containing all "n - k + 1" hash values contained within the data stream, and the positions associated with them (in the same format as yielded by next.)

After calling "values()" the stream will be completely exhausted, causing subsequent calls to "values" and "next()" to return "undef".

NOTE: You should use "next" if your source stream is infinite, as values will greedily attempt to consume all values.

BUGS

SEE ALSO

  "Winnowing: Local Algorithms for Document Fingerprinting"
  L<http://theory.stanford.edu/~aiken/publications/papers/sigmod03.pdf>

  Wikipedia: Rabin-Karp string search algorithm
  L<http://en.wikipedia.org/wiki/Rabin-Karp>

AUTHOR

  Norman Nunley E<lt>nnunley@gmail.comE<gt>
  Nicholas Clark (Who paired with me)