CF4J: Collaborative filtering for Java
CF4J is presented, a Java library designed to carry out Collaborative Filtering based RS research experiments and serves as a library specifically designed for the research trial and error process.
Abstract
Recommender Systems (RS) provide a relevant tool to mitigate the information\noverload problem. A large number of researchers have published hundreds of\npapers to improve different RS features. It is advisable to use RS frameworks\nthat simplify RS researchers: a) to design and implement recommendations\nmethods and, b) to speed up the execution time of the experiments. In this\npaper, we present CF4J, a Java library designed to carry out Collaborative\nFiltering based RS research experiments. CF4J has been designed from\nresearchers to researchers. It allows: a) RS datasets reading, b) full and easy\naccess to data and intermediate or final results, c) to extend their main\nfunctionalities, d) to concurrently execute the implemented methods, and e) to\nprovide a thorough evaluation for the implementations by quality measures. In\nsummary, CF4J serves as a library specifically designed for the research trial\nand error process.\n