ActsAsRecommendable

ActsAsRecommendable is a plugin for Rails that simplifies collaborative filtering

The plugin provides a mechanism for finding loose associations between users and items which we can tell you

• Given a user, return other similar users based on what items they have all bought/bookmarked/rated/etc
• Given a user, return recommended items based on the items bought/bookmarked/rated/etc by that user and the items bought/bookmarked/rated/etc by other users.

The plugin calculations can be made online and offline and stored using the rails cache (such as memcache) for online retrieval. Online retrieval of recommendations uses item-based collaborative filtering using the offline items similarity matrix stored in the cache. This can give up-to-date results with a much lower processing overhead.

Much thanks to Toby Segaran and his excellent book Programming Collective Intelligence (http://oreilly.com/catalog/9780596529321/).

Features

Use join rating scores Using abitary calculated scores Similar Items Recommended Users Cached dataset

Current Release

v0.1 should be considered early alpha and not ready for production applications.

Lots of performance optimisations still to be done.

Example

class Book < ActiveRecord::Base has_many :user_books has_many :users, :through => :user_books end

class UserBook < ActiveRecord::Base belongs_to :book belongs_to :user end

class User < ActiveRecord::Base has_many :user_books has_many :books, :through => :user_books acts_as_recommendable :books, :through => :user_books end

user = User.find(:first) user.similar_users #=> [...] user.recommended_books #=> [...]

book = Book.find(:first) book.similar_books #=> [...]

Example 2

class Movie < ActiveRecord::Base has_many :user_movies has_many :users, :through => :user_movies end

class UserMovie < ActiveRecord::Base belongs_to :movie belongs_to :user end

class User < ActiveRecord::Base has_many :user_movies has_many :movies, :through => :user_movies acts_as_recommendable :movies, :through => :user_movies, :score => :score

'score' is an attribute on the users_movies table

end

user = User.find(:first) user.similar_users #=> [...] user.recommended_movies #=> [...]

Example 3

class Book < ActiveRecord::Base has_many :user_books has_many :users, :through => :user_books, :use_dataset => true

Uses cached dataset

end

class UserBook < ActiveRecord::Base belongs_to :book belongs_to :user end

class User < ActiveRecord::Base has_many :user_books has_many :books, :through => :user_books acts_as_recommendable :books, :through => :user_books end

user = User.find(:first) user.recommended_books #=> [...]

The example above uses a cached dataset.

You need to generate a cached dataset every so often (depending on how much your content changes)

You can do that by calling the rake task recommendations:build, you should run this with a cron job every so often.

If you only want to use the dataset in production put this in production.rb:

User.aar_options[:use_dataset] = true

Note:

user.similar_users doesn't use the dataset

The advantage of using a dataset is that you don't need to load all the users & items into

memory (which you do normally). The disadvantage is that you won't get as accurate results.

Contact

[email protected]

Copyright (c) 2008 Made by Many Ltd, released under the MIT license