Case recommender

• DOI: 10.1145/3240323.3241611
• Publication Date: 2018-09-28T14:00:41Z
• Authors: Arthur da Costa; Eduardo Fressato; Fernando Neto; Marcelo Manzato; Ricardo Campello
• Keywords: 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology

This paper presents a polished open-source Python-based recommender framework named Case Recommender, which provides a rich set of components from which developers can construct and evaluate customized recommender systems. It implements well-known and state-of-the-art algorithms in rating prediction and item recommendation scenarios. The main advantage of the Case Recommender is the possibility to integrate clustering and ensemble algorithms with recommendation engines, easing the development of more accurate and efficient approaches.