{"id":15700282,"url":"https://github.com/soumik12345/multi-label-text-classification","last_synced_at":"2025-08-16T23:44:27.653Z","repository":{"id":46687178,"uuid":"409111837","full_name":"soumik12345/multi-label-text-classification","owner":"soumik12345","description":"A multi-label text classifier to predict the subject areas of arXiv papers from their abstract bodies.","archived":false,"fork":false,"pushed_at":"2021-10-06T15:37:37.000Z","size":245,"stargazers_count":17,"open_issues_count":0,"forks_count":4,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-05-12T13:12:22.575Z","etag":null,"topics":["deep-learning","text-classification"],"latest_commit_sha":null,"homepage":"https://keras.io/examples/nlp/multi_label_classification/","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/soumik12345.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2021-09-22T07:49:56.000Z","updated_at":"2024-10-06T22:41:06.000Z","dependencies_parsed_at":"2022-09-23T19:13:09.571Z","dependency_job_id":null,"html_url":"https://github.com/soumik12345/multi-label-text-classification","commit_stats":null,"previous_names":[],"tags_count":3,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/soumik12345%2Fmulti-label-text-classification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/soumik12345%2Fmulti-label-text-classification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/soumik12345%2Fmulti-label-text-classification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/soumik12345%2Fmulti-label-text-classification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/soumik12345","download_url":"https://codeload.github.com/soumik12345/multi-label-text-classification/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":253745195,"owners_count":21957319,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":["deep-learning","text-classification"],"created_at":"2024-10-03T19:47:41.335Z","updated_at":"2025-05-12T13:12:41.802Z","avatar_url":"https://github.com/soumik12345.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Multi-label Text Classification\n\nHolds code for collecting data from arXiv to build a multi-label text classification dataset and a simpler classifier on\ntop of that. Our dataset is now [available on Kaggle](https://www.kaggle.com/spsayakpaul/arxiv-paper-abstracts). The dataset collection process\nhas been shown in [this notebook](https://github.com/soumik12345/multi-label-text-classification/blob/master/beam_arxiv_scrape.ipynb). We leverage\nApache Beam to design our data collection pipeline and our pipeline can be run on [Dataflow](https://cloud.google.com/dataflow) at scale. We hope\nthe data will be a useful benchmark for building multi-label text classification systems.\n\nHere's an accompanying blog post on keras.io discussing the motivation behind this dataset, building a simple\nbaseline model, etc.: [Large-scale multi-label text classification](https://keras.io/examples/nlp/multi_label_classification/).\n\n## Acknowledgements\n\nWe would like to thank [Matt Watson](https://github.com/mattdangerw) for helping us build the simple baseline classifier model. Thanks to\n[Lukas Schwab](https://github.com/lukasschwab) (author of [`arxiv.py`](https://github.com/lukasschwab/arxiv.py)) for helping us build\nour initial data collection utilities. Thanks to [Robert Bradshaw](https://www.linkedin.com/in/robert-bradshaw-1b48a07/) for his inputs\non the Apache Beam pipeline. Thanks to the [ML-GDE program](https://developers.google.com/programs/experts/) for providing GCP credits\nthat allowed us to run the Beam pipeline at scale on Dataflow.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsoumik12345%2Fmulti-label-text-classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsoumik12345%2Fmulti-label-text-classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsoumik12345%2Fmulti-label-text-classification/lists"}