{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/pyreclab-a-software-library-for-quick","title":"pyRecLab: A Software Library for Quick Prototyping of Recommender Systems","arxiv_id":"1706.06291","date":"2017-06-20","proceeding":null,"authors":["Gabriel Sepulveda","Vicente Dominguez","Denis Parra"],"abstract":"This paper introduces pyRecLab, a software library written in C++ with Python\nbindings which allows to quickly train, test and develop recommender systems.\nAlthough there are several software libraries for this purpose, only a few let\ndevelopers to get quickly started with the most traditional methods, permitting\nthem to try different parameters and approach several tasks without a\nsignificant loss of performance. Among the few libraries that have all these\nfeatures, they are available in languages such as Java, Scala or C#, what is a\ndisadvantage for less experienced programmers more used to the popular Python\nprogramming language. In this article we introduce details of pyRecLab, showing\nas well performance analysis in terms of error metrics (MAE and RMSE) and\ntrain/test time. We benchmark it against the popular Java-based library LibRec,\nshowing similar results. We expect programmers with little experience and\npeople interested in quickly prototyping recommender systems to be benefited\nfrom pyRecLab.","url_abs":"http://arxiv.org/abs/1706.06291v2","url_pdf":"http://arxiv.org/pdf/1706.06291v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"pyreclab-a-software-library-for-quick","repo_url":"https://github.com/gasevi/pyreclab","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"recommendation-systems","task_name":"Recommendation Systems"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}