opencf

OpenCF

PHP implementation of the (Weighted Slopeone,Cosine, Weighted Cosine) rating-based collaborative filtering schemes.

To learn all about it, head over to the extensive documentation.

Installation

OpenCF Package requires PHP 7.4 or higher.

INFO: If you are using an older version of php this package will not function correctly.

The supported way of installing OpenCF package is via Composer.

composer require phpjuice/opencf

Usage

OpenCF Package is designed to be very simple and straightforward to use. All you have to do is:

1. Load a training set (dataset)
2. Predict future ratings using a recommender. (Weighted Slopeone,Cosine, Weighted Cosine)

Create Recommender Service

The OpenCF recommender service is created by direct instantiation:

use OpenCF\RecommenderService;

// Create an instance
$recommenderService = new RecommenderService($dataset);

Adding dataset

Adding a dataset to the recommender can be done using the constructor or can be easily done by providing an array of users ratings via the setDataset() method:

$dataset = [
    "squid" => [
        "user1" => 1,
        "user2" => 1,
        "user3" => 0.2,
    ],
    "cuttlefish" => [
        "user1" => 0.5,
        "user3" => 0.4,
        "user4" => 0.9,
    ],
    "octopus" => [
        "user1" => 0.2,
        "user2" => 0.5,
        "user3" => 1,
        "user4" => 0.4,
    ],
    "nautilus" => [
        "user2" => 0.2,
        "user3" => 0.4,
        "user4" => 0.5,
    ],
];

$recommenderService->setDataset($dataset);

Getting Predictions

All you have to do to predict ratings for a new user is to retrieve an engine from the recommender service and & run the predict() method.

// Get a recommender
$recommender = $recommenderService->cosine(); // Cosine recommender
// OR
$recommender = $recommenderService->weightedCosine(); // WeightedCosine recommender
// OR
$recommender = $recommenderService->weightedSlopeone(); // WeightedSlopeone recommender

// Predict future ratings
$results = $recommender->predict([
    "squid" => 0.4
]);

This should produce the following results when using WeightedSlopeone recommender

[
  "cuttlefish" => 0.25,
  "octopus" => 0.23,
  "nautilus" => 0.1
];

Running the tests

you can easily run tests using composer

composer test

Built With

• PHP - The programing language used
• Composer - Dependency Management
• Pest - An elegant PHP Testing Framework

Changelog

Please see the changelog for more information on what has changed recently.

Contributing

Please see CONTRIBUTING.md for details and a todo list.

Security

If you discover any security related issues, please email author instead of using the issue tracker.

Credits

• Daniel Lemire
• SlopeOne Predictors for Online Rating-Based Collaborative Filtering
• Distance Weighted Cosine Similarity

Versioning

We use SemVer for versioning. For the versions available, see the tags on this repository.

License

license. Please see the Licence for more information.

This site is open source. Improve this page.