NAME
   Algorithm::SlopeOne - Slope One collaborative filtering for rated
   resources

VERSION
   version 0.002

SYNOPSIS
       #!/usr/bin/env perl
       use common::sense;
       use Algorithm::SlopeOne;
       use Data::Printer;

       my $s = Algorithm::SlopeOne->new;
       $s->update([
           {
               squid       => 1.0,
               cuttlefish  => 0.5,
               octopus     => 0.2,
           }, {
               squid       => 1.0,
               octopus     => 0.5,
               nautilus    => 0.2,
           }, {
               squid       => 0.2,
               octopus     => 1.0,
               cuttlefish  => 0.4,
               nautilus    => 0.4,
           }, {
               cuttlefish  => 0.9,
               octopus     => 0.4,
               nautilus    => 0.5,
           },
       ]);
       p $s->predict({ squid => 0.4 });

       # Output:
       # \ {
       #     cuttlefish   0.25,
       #     nautilus     0.1,
       #     octopus      0.233333333333333
       # }

DESCRIPTION
   Perl implementation of the *Weighted Slope One* rating-based
   collaborative filtering scheme.

ATTRIBUTES
 diffs
   Differential ratings matrix.

 freqs
   Ratings count matrix.

METHODS
 clear
   Reset the instance.

 update($userprefs)
   Update matrices with user preference data, accepts a HashRef or an
   ArrayRef of HashRefs:

       $s->predict({ StarWars => 5, LOTR => 5, StarTrek => 3, Prometheus => 1 });
       $s->predict({ StarWars => 3, StarTrek => 5, Prometheus => 4 });
       $s->predict([
           { IronMan => 4, Avengers => 5, XMen => 3 },
           { XMen => 5, DarkKnight => 5, SpiderMan => 3 },
       ]);

 predict($userprefs)
   Recommend new items given known item ratings.

       $s->predict({ StarWars => 5, LOTR => 5, Prometheus => 1 });

REFERENCES
   *   Slope One <https://en.wikipedia.org/wiki/Slope_One> - Wikipedia
       article

   *   Slope One Predictors for Online Rating-Based Collaborative Filtering
       <http://lemire.me/fr/abstracts/SDM2005.html> - original paper

   *   Collaborative filtering made easy
       <http://www.serpentine.com/blog/2006/12/12/collaborative-filtering-m
       ade-easy/> - Python implementation by Bryan O'Sullivan (primary
       reference, test code)

   *   github.com/ashleyw/Slope-One <https://github.com/ashleyw/Slope-One>
       - Ruby port of the above by Ashley Williams (used to borrow test
       code)

   *   Programming Collective Intelligence book
       <http://shop.oreilly.com/product/9780596529321.do> by Toby Segaran

   *   Data Sets by GroupLens Research <http://www.grouplens.org/node/12>

AUTHOR
   Stanislaw Pusep <[email protected]>

COPYRIGHT AND LICENSE
   This software is copyright (c) 2012 by Stanislaw Pusep.

   This is free software; you can redistribute it and/or modify it under
   the same terms as the Perl 5 programming language system itself.