Warning

Docs are complete, but revision is still a Work in Progress. Sorry for any typos!

Welcome to ClayRS's documentation!

        

ClayRS is a python framework for (mainly) content-based recommender systems which allows you to perform several operations, starting from a raw representation of users and items to building and evaluating a recommender system. It also supports graph-based recommendation with feature selection algorithms and graph manipulation methods.

The framework has three main modules, which you can also use individually:

Given a raw source, the Content Analyzer:

• Creates and serializes contents,
• Using the chosen configuration

The RecSys module allows to:

• Instantiate a recommender system
  • Using items and users serialized by the Content Analyzer
• Make score prediction or recommend items for the active user(s)

The EvalModel has the task of evaluating a recommender system, using several state-of-the-art metrics

The various sections of this documentation will guide you in becoming a full expert of ClayRS!