{"id":41053550,"url":"https://github.com/usaito/unbiased-pairwise-rec","last_synced_at":"2026-01-22T11:30:57.835Z","repository":{"id":39731696,"uuid":"232191992","full_name":"usaito/unbiased-pairwise-rec","owner":"usaito","description":"(ICTIR2020) \"Unbiased Pairwise Learning from Biased Implicit Feedback\"","archived":false,"fork":false,"pushed_at":"2022-11-21T21:55:20.000Z","size":29,"stargazers_count":17,"open_issues_count":6,"forks_count":5,"subscribers_count":2,"default_branch":"master","last_synced_at":"2023-03-05T13:18:11.861Z","etag":null,"topics":["bayesian-personalized-ranking","implicit-feedback","recommender-system","research"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/usaito.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-01-06T21:51:44.000Z","updated_at":"2023-03-05T06:16:07.000Z","dependencies_parsed_at":"2023-01-22T04:47:22.646Z","dependency_job_id":null,"html_url":"https://github.com/usaito/unbiased-pairwise-rec","commit_stats":null,"previous_names":[],"tags_count":null,"template":null,"template_full_name":null,"purl":"pkg:github/usaito/unbiased-pairwise-rec","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/usaito%2Funbiased-pairwise-rec","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/usaito%2Funbiased-pairwise-rec/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/usaito%2Funbiased-pairwise-rec/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/usaito%2Funbiased-pairwise-rec/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/usaito","download_url":"https://codeload.github.com/usaito/unbiased-pairwise-rec/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/usaito%2Funbiased-pairwise-rec/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28662085,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-22T01:17:37.254Z","status":"online","status_checked_at":"2026-01-22T02:00:07.137Z","response_time":144,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["bayesian-personalized-ranking","implicit-feedback","recommender-system","research"],"created_at":"2026-01-22T11:30:57.764Z","updated_at":"2026-01-22T11:30:57.830Z","avatar_url":"https://github.com/usaito.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"## Unbiased Pairwise Learning from Biased Implicit Feedback\n\n---\n\n### About\n\nThis repository accompanies the real-world experiments conducted in the paper \"**Unbiased Pairwise Learning from Biased Implicit Feedback**\" by [Yuta Saito](https://usaito.github.io/), which has been accepted by [ICTIR'20](https://ictir2020.org/).\n\n\u003c!-- If you find this code useful in your research then please cite:\n\n```\n@\n``` --\u003e\n\n\n### Dependencies\n\n- python\u003e=3.7\n- numpy==1.18.1\n- pandas==0.25.1\n- scikit-learn==0.23.1\n- tensorflow==1.15.2\n- pyyaml==5.1.2\n\n### Datasets\nTo run the simulation with real-world datasets, the following datasets need to be prepared as described below.\n\n- download the [Yahoo! R3 dataset](https://webscope.sandbox.yahoo.com/catalog.php?datatype=r) and put `train.txt` and `test.txt` files into `./data/yahoo/raw/` directory.\n- download the [Coat dataset](https://www.cs.cornell.edu/~schnabts/mnar/) and put `train.ascii` and `test.ascii` files into `./data/coat/raw/` directory.\n\n### Running the code\n\nFirst, to preprocess the datasets, navigate to the `src/` directory and run the command\n\n```bash\npython preprocess_datasets.py -d coat yahoo\n```\n\nThen, run the following command in the same directory\n\n```bash\nfor data in yahoo coat\n  do\n  for model in wmf expomf crmf bpr ubpr\n  do\n    python main.py -m $model -d $data -r 10\n  done\ndone\n```\n\nThis will run real-world experiments conducted in Section 4.\nAfter running the experimens, you can summarize the results by running the following command in the `src/` directory.\n\n```bash\npython summarize_results.py -d yahoo coat\n```\n\nOnce the code is finished executing, you can find the summarized results in `./paper_results/` directory.\n\n\n### Acknowledgement\n\nWe thank [Minato Sato](https://github.com/satopirka) for his helpful comments, discussions, and advice.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fusaito%2Funbiased-pairwise-rec","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fusaito%2Funbiased-pairwise-rec","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fusaito%2Funbiased-pairwise-rec/lists"}