Skip to main content
Help us improve PyPI by participating in user testing. All experience levels needed!

Python wrapper for the SUGGEST, which is a Top-N recommendation engine that implements a variety of recommendation algorithms for collaborative filtering.

Project description

Python wrapper by Ricardo Niederberger Cabral (ricardo.cabral at imgseek.net).

Recommendation engine by George Karypis (http://glaros.dtc.umn.edu/gkhome/suggest/overview).

More about the wrapped library (SUGGEST):

SUGGEST is a Top-N recommendation engine that implements a variety of recommendation algorithms. Top-N recommender systems, a personalized information filtering technology, are used to identify a set of N items that will be of interest to a certain user. In recent years, top-N recommender systems have been used in a number of different applications such to recommend products a customer will most likely buy; recommend movies, TV programs, or music a user will find enjoyable; identify web-pages that will be of interest; or even suggest alternate ways of searching for information.

The algorithms implemented by SUGGEST are based on collaborative filtering that is the most successful and widely used framework for building recommender systems. SUGGEST implements two classes of collaborative filtering-based top-N recommendation algorithms, called user-based and item-based.

Project details


Release history Release notifications

This version
History Node

1.0

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging CloudAMQP CloudAMQP RabbitMQ AWS AWS Cloud computing Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page