{"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/towards-knowledge-based-recommender-dialog","title":"Towards Knowledge-Based Recommender Dialog System","arxiv_id":"1908.05391","date":"2019-08-15","proceeding":"IJCNLP 2019 11","authors":["Qibin Chen","Junyang Lin","Yichang Zhang","Ming Ding","Yukuo Cen","Hongxia Yang","Jie Tang"],"abstract":"In this paper, we propose a novel end-to-end framework called KBRD, which stands for Knowledge-Based Recommender Dialog System. It integrates the recommender system and the dialog generation system. The dialog system can enhance the performance of the recommendation system by introducing knowledge-grounded information about users' preferences, and the recommender system can improve that of the dialog generation system by providing recommendation-aware vocabulary bias. Experimental results demonstrate that our proposed model has significant advantages over the baselines in both the evaluation of dialog generation and recommendation. A series of analyses show that the two systems can bring mutual benefits to each other, and the introduced knowledge contributes to both their performances.","url_abs":"https://arxiv.org/abs/1908.05391v2","url_pdf":"https://arxiv.org/pdf/1908.05391v2.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":"towards-knowledge-based-recommender-dialog","repo_url":"https://github.com/THUDM/KBRD","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"recommendation-systems","task_name":"Recommendation Systems"},{"task_slug":"text-generation","task_name":"Text Generation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/recommendation-systems-on-redial","task":"Recommendation Systems","dataset":"ReDial","model":"KBRD","rank_in_archive_order":7,"of":8,"metrics":{"Recall@1":"0.03","Recall@10":"0.163","Recall@50":"0.338"},"uses_additional_data":false},{"leaderboard":"/sota/text-generation-on-redial","task":"Text Generation","dataset":"ReDial","model":"KBRD","rank_in_archive_order":5,"of":5,"metrics":{"Distinct-3":"0.3","Distinct-4":"0.45","Perplexity":"17.9"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1908.05391","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}