{"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/song-recommendation-with-non-negative-matrix","title":"Song Recommendation with Non-Negative Matrix Factorization and Graph Total Variation","arxiv_id":"1601.01892","date":"2016-01-08","proceeding":null,"authors":["Kirell Benzi","Vassilis Kalofolias","Xavier Bresson","Pierre Vandergheynst"],"abstract":"This work formulates a novel song recommender system as a matrix completion\nproblem that benefits from collaborative filtering through Non-negative Matrix\nFactorization (NMF) and content-based filtering via total variation (TV) on\ngraphs. The graphs encode both playlist proximity information and song\nsimilarity, using a rich combination of audio, meta-data and social features.\nAs we demonstrate, our hybrid recommendation system is very versatile and\nincorporates several well-known methods while outperforming them. Particularly,\nwe show on real-world data that our model overcomes w.r.t. two evaluation\nmetrics the recommendation of models solely based on low-rank information,\ngraph-based information or a combination of both.","url_abs":"http://arxiv.org/abs/1601.01892v2","url_pdf":"http://arxiv.org/pdf/1601.01892v2.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":"song-recommendation-with-non-negative-matrix","repo_url":"https://github.com/kikohs/recog","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"collaborative-filtering","task_name":"Collaborative Filtering"},{"task_slug":"matrix-completion","task_name":"Matrix Completion"},{"task_slug":"recommendation-systems","task_name":"Recommendation Systems"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1601.01892","atlas_url":"https://app.syntology.ai/?focus=1601.01892","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}