We introduce rrecsys, an extension package in R for rapid prototyping and intuitive assessment of recommender system algorithms. Due to its wide variety of implemented packages and functionalities, R language represents a popular choice for many tasks in Data Analysis. As the only currently available R package for recommender algorithms (recommenderlab) does not include popular algorithm implementations such as matrix factorization or algorithms for binarized rating data we developed rrecsys as an easily accessible tool that can, for instance, be employed for interactive demonstrations when teaching.
This package replicates the most popular collaborative filtering algorithms for rating and binary data and we compare results with the Java-based LensKit implementation for the purpose of benchmarking the implementation. Therefore this work must also be seen as a contribution in the context of replication of algorithm implementations and reproduction of evaluation results. Users can easily tune available implementations or develop their own algorithms and assess them according to the standard methodology for offline evaluation. Thus this package should represent an easily accessible environment for research and teaching purposes in the field of recommender systems.
Ludovik Çoba is an assitant-lecturer of Informatics at the University of Shkodra “Luigj Gurakuqi”, Albania. He received his BSc. and MSc. in Computer Engineering at the University of Padua(Italy) before becoming an IT specialist at the University of Shkodra in 2012. In a short period he was promoted to chief of the IT division at the same institute and soon he was invited to lecture at the Polytechnic University of Tirana. By the end of 2013 he moved to a full time assitant-lecturer position at the department of Computer Sciences at University of Shkodra. His current field of research is on recommender systems.