{"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-deep-conversational-recommendations","title":"Towards Deep Conversational Recommendations","arxiv_id":"1812.07617","date":"2018-12-18","proceeding":"NeurIPS 2018 12","authors":["Raymond Li","Samira Kahou","Hannes Schulz","Vincent Michalski","Laurent Charlin","Chris Pal"],"abstract":"There has been growing interest in using neural networks and deep learning\ntechniques to create dialogue systems. Conversational recommendation is an\ninteresting setting for the scientific exploration of dialogue with natural\nlanguage as the associated discourse involves goal-driven dialogue that often\ntransforms naturally into more free-form chat. This paper provides two\ncontributions. First, until now there has been no publicly available\nlarge-scale dataset consisting of real-world dialogues centered around\nrecommendations. To address this issue and to facilitate our exploration here,\nwe have collected ReDial, a dataset consisting of over 10,000 conversations\ncentered around the theme of providing movie recommendations. We make this data\navailable to the community for further research. Second, we use this dataset to\nexplore multiple facets of conversational recommendations. In particular we\nexplore new neural architectures, mechanisms, and methods suitable for\ncomposing conversational recommendation systems. Our dataset allows us to\nsystematically probe model sub-components addressing different parts of the\noverall problem domain ranging from: sentiment analysis and cold-start\nrecommendation generation to detailed aspects of how natural language is used\nin this setting in the real world. We combine such sub-components into a\nfull-blown dialogue system and examine its behavior.","url_abs":"http://arxiv.org/abs/1812.07617v2","url_pdf":"http://arxiv.org/pdf/1812.07617v2.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-deep-conversational-recommendations","repo_url":"https://github.com/RaymondLi0/conversational-recommendations","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"conversational-recommendation","task_name":"Conversational Recommendation"},{"task_slug":"recommendation-systems","task_name":"Recommendation Systems"},{"task_slug":"sentiment-analysis","task_name":"Sentiment Analysis"}],"methods":[],"datasets_introduced":[{"slug":"redial","name":"ReDial","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1812.07617","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1812.07617"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/RaymondLi0/conversational-recommendations","reach":null}],"summary":{"ran_violates":1},"by_repo_kind":{"listed":{"samples":1,"ran":1,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":1,"samples":[{"code_sha256_prefix":"772e03efcfe35812","entry":"train","repo":"RaymondLi0/conversational-recommendations","repo_kind":"listed","path":"train_recommender.py","file_url":"https://github.com/RaymondLi0/conversational-recommendations/blob/HEAD/train_recommender.py","link_basis":"first_harvest_node","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"772e03efcfe35812"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}