{"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/explainable-recommendation-via-multi-task","title":"Explainable Recommendation via Multi-Task Learning in Opinionated Text Data","arxiv_id":"1806.03568","date":"2018-06-10","proceeding":null,"authors":["Nan Wang","Hongning Wang","Yiling Jia","Yue Yin"],"abstract":"Explaining automatically generated recommendations allows users to make more\ninformed and accurate decisions about which results to utilize, and therefore\nimproves their satisfaction. In this work, we develop a multi-task learning\nsolution for explainable recommendation. Two companion learning tasks of user\npreference modeling for recommendation} and \\textit{opinionated content\nmodeling for explanation are integrated via a joint tensor factorization. As a\nresult, the algorithm predicts not only a user's preference over a list of\nitems, i.e., recommendation, but also how the user would appreciate a\nparticular item at the feature level, i.e., opinionated textual explanation.\nExtensive experiments on two large collections of Amazon and Yelp reviews\nconfirmed the effectiveness of our solution in both recommendation and\nexplanation tasks, compared with several existing recommendation algorithms.\nAnd our extensive user study clearly demonstrates the practical value of the\nexplainable recommendations generated by our algorithm.","url_abs":"http://arxiv.org/abs/1806.03568v1","url_pdf":"http://arxiv.org/pdf/1806.03568v1.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":"explainable-recommendation-via-multi-task","repo_url":"https://github.com/mythwn/mter","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"explainable-recommendation","task_name":"Explainable Recommendation"},{"task_slug":"multi-task-learning","task_name":"Multi-Task Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1806.03568","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}