Text::NSP::Measures - Perl modules for computing association scores of Ngrams. This module provides the basic framework for these measures.


Basic Usage

  use Text::NSP::Measures::2D::MI::ll;

  my $ll = Text::NSP::Measures::2D::MI::ll->new();

  $ll_value = $ll->calculateStatistic( n11=>10,

  if( ($errorCode = $ll->getErrorCode()))
    print STDERR $erroCode." - ".$ll->getErrorMessage();
    print $ll->getStatisticName."value for bigram is ".$ll_value;



These modules provide perl implementations of mathematical functions (association measures) that can be used to interpret the cooccurrence frequency data for Ngrams. We define an Ngram as a sequence of 'n' tokens that occur within a window of at least 'n' tokens in the text; what constitutes a "token" can be defined by the user.

The measures that have been implemented in this distribution are:

1) MI (Mutual Information based Measures)
a) Loglikelihood (for Bigrams and Trigrams)
b) True Mutual Information (for Bigrams and Trigrams)
c) Pointwise Mutual Information (for Bigrams and Trigrams)
d) Poisson Stirling Measure (for Bigrams and Trigrams)
2) CHI (Measures belonging to the CHI family)
a) Chi-squared Measure
b) Phi Coefficient
c) T-Score
3) Dice (Measures belonging to the Dice family)
a) Dice Coefficient
b) Jaccard Measure
4) Fishers Exact Tests
a) Left Fishers Exact Test
b) Right Fishers Exact Test
c) Two-Tailed Fishers Exact Test
5) Odds Ratio

Further discussion about these measures is in their respective documentations.

Writing your own association measures

This module also provides a basic framework for building new measures of association for Ngrams. The new Measure should either inherit from Text::NSP::Measures::2D or Text::NSP::Measures::3D modules, depending on whether it is a bigram or a trigram measure. Both these modules implement methods that retrieve observed frequency counts, marginal totals, and also compute expected values. They also provide error checks for these counts.

You can either write your new measure as a new module, using Perl's Object Oriented concepts, or you can simply write a perl program. Here we will describe how to write a new measure using Object Oriented Perl.

  1. To create a new Perl module for the measure issue the following command (replace 'NewMeasure' with the name of your measure):

    h2xs -AXc -n Text::NSP::Measures::2D::NewMeasure (for bigram measures)


    h2xs -AXc -n Text::NSP::Measures::3D::NewMeasure (for trigram measures)

    This will create a new folder namely...

    Text-NSP-Measures-2D-NewMeasure (for bigram)


    Text-NSP-Measures-3D-NewMeasure (for trigram)

    This will create an empty framework for the new association measure. Once you are done completing the changes you will have to install the module before you can use it.

    To make changes to the module open:




    in your favorite text editor, and do as follows.

  2. Let us say you have named your module NewMeasure. The first line of the file should declare that it is a package. Thus the first line of the file should be...

       package Text::NSP::Measures::2D::NewMeasure; (for bigram measures)
       package Text::NSP::Measures::3D::NewMeasure; (for trigram measures)
  3. To inherit the functionality from the 2D or 3D module you need to include it in your module.

    A small code snippet to ensure that it is included is as follows:

    1 For Bigrams
      use Text::NSP::Measures::2D;
      my @ISA;
      @ISA = qw(Text::NSP::Measures::2D);
    2 For Trigrams
      use Text::NSP::Measures::3D;
      my @ISA;
      @ISA = qw(Text::NSP::Measures::3D);
  4. You need to implement at least one method in your package

       i)  calculateStatistic()

    This method is passed an reference of a hash containing the frequency values for an Ngram as found in the input Ngram file.

    method calculateStatistic() is expected to return a (possibly floating) value as the value of the statistical measure calculated using the frequency values passed to it.

    The first line of code in calculateStatistic should be

      my $self = shift;

    this will store the reference of the object for the measure which was used to invoke calculateStatistic().

    There exist three methods in the modules Text::NSP::Measures::2d and Text::NSP::Measures::3D in order to help calculate the bigram statistic.

       1.  computeObservedValues($frequencies);
       2.  computeExpectedValues($frequencies);
       3.  computeMarginalTotals($frequencies);

    These methods return the observed and expected values of the cells in the contingency table. A 2D contingency table looks like:

                |word2  | not-word2|
        word1   | n11   |   n12    |  n1p
      not-word1 | n21   |   n22    |  n2p
                  np1       np2       npp

    Here the marginal totals are np1, n1p, np2, n2p, the Observed values are n11, n12, n21, n22 and the expected values for the corresponding observed values are represented using m11, m12, m21, m22, here m11 represents the expected value for the cell (1,1), m12 for the cell (1,2) and so on.

    The method computeObservedValues will return the observed values for the given Ngram. The observed values are stored in a hash and the reference to the hash is returned. If it does not then there existed an error in the calculation of these values and zero should be returned. An example of how this can be used is as follows:

      my $self = shift;
      my %values = @_;
      if( !($observed = $self->computeObservedValues(\%values) ) )

    where @_ is the parameters passed to calculateStatistic. And $self contains a reference to the measures object. The method returns referrence to a hash. This hash contains the key value pairs for the observed values. You can use these values in your code by:

        $observed->{n12} and so on for each cell in the contingency table.

    The method computeExpectedValues will return the list of expected values from the given Ngram. If it does not then there was an error in the calculation of these values and zero should be returned. An example of how this can be used is as follows:

      my $self = shift;
      my %values = @_;
      if( !($expected = $self->computeExpectedValues(\%values) ) )

    To use the expected values, you can

          $expected->{m12} and so on for the respective expected values

    Similarly the computeMarginalTotals method computes the marginal totals in the contingency table based on the observed frequencies. It also returns 0 in case of some error. An example of usage for the computeMarginalTotals() method is

      my $self = shift;
      my %values = @_;
      if( !($marginal = $self->computeMarginalTotals(\%values) ) )

    To use the returned values you can use

          $marginal->{m12} and so on for the respective marginal values

    The last lines of a module should always return true, to achieve this make sure that the last two lines of the are:


    Please see, that you can put in documentation after these lines.

    To tie it all together here is an example of a measure that computes the sum of ngram frequency counts.

    use Text::NSP::Measures::2D; use strict;

    our ($VERSION, @ISA);

    @ISA = qw(Text::NSP::Measures::2D::MI);

    $VERSION = '0.93';

    sub calculateStatistic { my $self = shift; my %values = @_;

      my $observed;
      # computes and returns the observed and expected values from
      # the frequency combination values. returns 0 if there is an
      # error in the computation or the values are inconsistent.
      if( !($observed = $self->computeObservedValues(\%values)) ) {
      #  Now for the actual calculation of the association measure
      my $NewMeasure = 0;
      $NewMeasure += $observed->{n11};
      $NewMeasure += $observed->{n12};
      $NewMeasure += $observed->{n21};
      $NewMeasure += $observed->{n22};
      return ( $NewMeasure );
  5. There are four other methods that are not mandatory, but may be implemented. These are:

         i) initializeStatistic()
        ii) getErrorCode
       iii) getErrorMessage
       iv) getStatisticName()

    Whenever an object of the measure is created the constructor will invoke the initializeStatistic() method, if there is no need for any specific initialization in the measure you need not define this method, and the initialization will be handled by the Text::NSP::Measures modules initializeStatistic() method.

    The getErrorCode method is called immediately after every call to method calculateStatistic(). This method is used to return the errorCode, if any, in the previous operations. To view all the possible errorcodes and the corresponding error message please reffer to the Text::NSP documentation (perldoc Text::NSP).You can create new errorcodes in your measure, if the existing errorcodes are not sufficient.

    The Text::NSP::Measures module implements both getErrorCode() and getErrorMessage() methods and these implementations of the method will be invoked if the user does not define these methods. But if you want to add some other actions that need to be performed in case of an error you must override these methods by implementing them in your module. You can invoke the Text::NSP::Measures getErrorCode() methods from your measures getErrorCode() method.

    An example of this is below:

      sub getErrorCode
        my $self = shift;
        my $code = $self->SUPER::getErrorCode();
        #your code here
        return $code; #(or any other value)
      sub getErrorMessage
        my $self = shift;
        my $message = $self->SUPER::getErrorMessage();
        #your code here
        return $message; #(or any other value)

    The fourth method that may be implemented is getStatisticName(). If this method is implemented, it is expected to return a string containing the name of the statistic being implmented. This string is used in the formatted output of If this method is not implemented, then the statistic name entered on the commandline is used in the formatted output.

    Note that all the methods described in this section are optional. So, if the user elects to not implement these methods, no harm will be done.

    The user may implement other methods too, but since is not expecting anything besides the five methods above, doing so would have no effect on

  6. You will need to install your module before you can use it. You can do this by

      Change to the base directory for the module, i.e.
      Then issue the following commands:
        perl Makefile.PL
        make test
        make install
        perl Makefile.PL PREFIX=<desination directory>
        make test
        make install

    If you get any errors in the installation process, please make sure that you have not made any syntactical error in your code and also make sure that you have already installed the Text-NSP package.

Errors to look out for:

  1. The Text-NSP package is not installed - Make sure that Text-NSP package is installed and you have inherited the correct module (Text::NSP::Measures::2D or Text::NSP::Measures::3D).

  2. The five methods (1 mandatory, 4 non-mandatory) must have their names match EXACTLY with those shown above. Again, names are all case sensitive.

  3. This statement is present at the end of the module: 1;


new() - In case user tries to create an object of the abstract class, this method is here to handle the error and print a small help.



initializeStatistic() - Provides an empty method which is called in case the measures do not override this method. If you need some measure specific initialization, override this method in yhe implementation of your measure.



calculateStatistic() - Provides an empty framework. Your Measure should override this method. INPUT PARAMS : none


getErrorCode() - Returns the error code in the last operation if any and resets the errorcode to 0.


# RETURN VALUES : errorCode .. The current error code.

getErrorMessage() - Returns the error message in the last operation if any and resets the string to ''.


# RETURN VALUES : errorMessage .. The current error message.


Ted Pedersen, University of Minnesota Duluth <>

Satanjeev Banerjee, Carnegie Mellon University <>

Amruta Purandare, University of Pittsburgh <>

Bridget Thomson-McInnes, University of Minnesota Twin Cities <>

Saiyam Kohli, University of Minnesota Duluth <>


Last updated: $Id:,v 1.15 2006/03/25 04:21:22 saiyam_kohli Exp $




Copyright (C) 2000-2006, Ted Pedersen, Satanjeev Banerjee, Amruta Purandare, Bridget Thomson-McInnes and Saiyam Kohli


Copyright (C) 2000-2006, Ted Pedersen, Satanjeev Banerjee, Amruta Purandare, Bridget Thomson-McInnes and Saiyam Kohli

This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.

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