  Recommender Systems (RS) provide a relevant tool to mitigate the information
overload problem. A large number of researchers have published hundreds of
papers to improve different RS features. It is advisable to use RS frameworks
that simplify RS researchers: a) to design and implement recommendations
methods and, b) to speed up the execution time of the experiments. In this
paper, we present CF4J, a Java library designed to carry out Collaborative
Filtering based RS research experiments. CF4J has been designed from
researchers to researchers. It allows: a) RS datasets reading, b) full and easy
access to data and intermediate or final results, c) to extend their main
functionalities, d) to concurrently execute the implemented methods, and e) to
provide a thorough evaluation for the implementations by quality measures. In
summary, CF4J serves as a library specifically designed for the research trial
and error process.
