{"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/mitigating-shortage-of-labeled-data-using","title":"Mitigating shortage of labeled data using clustering-based active learning with diversity exploration","arxiv_id":"2207.02964","date":"2022-07-06","proceeding":null,"authors":["Xuyang Yan","Shabnam Nazmi","Biniam Gebru","Mohd Anwar","Abdollah Homaifar","Mrinmoy Sarkar","Kishor Datta Gupta"],"abstract":"In this paper, we proposed a new clustering-based active learning framework, namely Active Learning using a Clustering-based Sampling (ALCS), to address the shortage of labeled data. 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