{"url":"/dataset/kkbox","name":"KKBox","full_name":null,"description_markdown":"The task is to predict the chances of a user listening to a song repetitively after the first observable listening event within a time window was triggered. If there are recurring listening event(s) triggered within a month after the user's very first observable listening event, its target is marked 1, and 0 otherwise in the training set. KKBox provides a training data set consists of information of the first observable listening event for each unique user-song pair within a specific time duration. Metadata of each unique user and song pair is also provided. The train and the test data are selected from users listening history in a given time period, and are split based on time. Note that only the labeled train set of the dataset is used for benchmarking.","description_withheld":null,"homepage":"https://www.kkbox.com/hk/tc/","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[{"name":"Click-Through Rate Prediction","url":"/task/click-through-rate-prediction","datasets_with_task":"/datasets/task/click-through-rate-prediction"}],"languages":[],"variants":["KKBox"],"data_loaders":[],"num_papers_in_archive":6,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/click-through-rate-prediction-on-kkbox","task":"Click-Through Rate Prediction","dataset_variant":"KKBox","rows":6,"metrics":["AUC"],"first_row_in_archive_order":{"model":"FCN","paper":"/paper/dcnv3-towards-next-generation-deep-cross","metrics":{"AUC":"0.8557"},"code_links":[{"title":"reczoo/FuxiCTR","url":"https://github.com/reczoo/FuxiCTR"},{"title":"salmon1802/DCNv3","url":"https://github.com/salmon1802/DCNv3"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/dcnv3-towards-next-generation-deep-cross","title":"FCN: Fusing Exponential and Linear Cross Network for Click-Through Rate Prediction","date":"2024-07-18","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/dcn-m-improved-deep-cross-network-for-feature","title":"DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems","date":"2020-08-19","rows_on_this_dataset":1,"code_links":12,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":14,"samples_ran":2,"samples_unverified":12,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/deep-interaction-machine-a-simple-but-1","title":"Deep Interaction Machine: A Simple but Effective Model for High-order Feature Interactions","date":"2020-01-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/autoint-automatic-feature-interaction","title":"AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks","date":"2018-10-29","rows_on_this_dataset":1,"code_links":19,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":0,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/xdeepfm-combining-explicit-and-implicit","title":"xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems","date":"2018-03-14","rows_on_this_dataset":1,"code_links":19,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":15,"samples_ran":3,"samples_unverified":12,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/deepfm-a-factorization-machine-based-neural","title":"DeepFM: A Factorization-Machine based Neural Network for CTR Prediction","date":"2017-03-13","rows_on_this_dataset":1,"code_links":23,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":8,"samples_ran":2,"samples_unverified":6,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":4,"samples_harvested":40,"samples_ran":7,"samples_unverified":33,"pointer_only_for_licence":4,"papers_with_no_sample_that_ran":1,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}