{"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/kuairec-a-fully-observed-dataset-for","title":"KuaiRec: A Fully-observed Dataset and Insights for Evaluating Recommender Systems","arxiv_id":"2202.10842","date":"2022-02-22","proceeding":null,"authors":["Chongming Gao","Shijun Li","Wenqiang Lei","Jiawei Chen","Biao Li","Peng Jiang","Xiangnan He","Jiaxin Mao","Tat-Seng Chua"],"abstract":"The progress of recommender systems is hampered mainly by evaluation as it requires real-time interactions between humans and systems, which is too laborious and expensive. This issue is usually approached by utilizing the interaction history to conduct offline evaluation. However, existing datasets of user-item interactions are partially observed, leaving it unclear how and to what extent the missing interactions will influence the evaluation. To answer this question, we collect a fully-observed dataset from Kuaishou's online environment, where almost all 1,411 users have been exposed to all 3,327 items. To the best of our knowledge, this is the first real-world fully-observed data with millions of user-item interactions. With this unique dataset, we conduct a preliminary analysis of how the two factors - data density and exposure bias - affect the evaluation results of multi-round conversational recommendation. Our main discoveries are that the performance ranking of different methods varies with the two factors, and this effect can only be alleviated in certain cases by estimating missing interactions for user simulation. This demonstrates the necessity of the fully-observed dataset. We release the dataset and the pipeline implementation for evaluation at https://kuairec.com","url_abs":"https://arxiv.org/abs/2202.10842v3","url_pdf":"https://arxiv.org/pdf/2202.10842v3.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":"kuairec-a-fully-observed-dataset-for","repo_url":"https://github.com/chongminggao/KuaiRec","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"CC-BY-SA-4.0"}},{"paper_slug":"kuairec-a-fully-observed-dataset-for","repo_url":"https://github.com/xiwenchao/fully_observed_demo","is_official":0,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"kuairec-a-fully-observed-dataset-for","repo_url":"https://github.com/chongminggao/cirs-codes","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"conversational-recommendation","task_name":"Conversational Recommendation"},{"task_slug":"recommendation-systems","task_name":"Recommendation Systems"},{"task_slug":"user-simulation","task_name":"User Simulation"}],"methods":[],"datasets_introduced":[{"slug":"kuairec","name":"KuaiRec","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2202.10842","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.10842"}},"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/chongminggao/KuaiRec","reach":{"status":"ok","spdx":"CC-BY-SA-4.0"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/chongminggao/cirs-codes","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/xiwenchao/fully_observed_demo","reach":null}],"summary":{"ran_honours":1},"by_repo_kind":{"named_in_paper":{"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":"fa61a78fb13efa2e","entry":"cuda_","repo":"xiwenchao/fully_observed_demo","repo_kind":"named_in_paper","path":"Multi_target/Popularity_Popularity_multi/run_6.py","file_url":"https://github.com/xiwenchao/fully_observed_demo/blob/HEAD/Multi_target/Popularity_Popularity_multi/run_6.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"fa61a78fb13efa2e"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}