{"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/finding-better-active-learners-for-faster","title":"Finding Better Active Learners for Faster Literature Reviews","arxiv_id":"1612.03224","date":"2016-12-10","proceeding":null,"authors":["Zhe Yu","Nicholas A. Kraft","Tim Menzies"],"abstract":"Literature reviews can be time-consuming and tedious to complete. By\ncataloging and refactoring three state-of-the-art active learning techniques\nfrom evidence-based medicine and legal electronic discovery, this paper finds\nand implements FASTREAD, a faster technique for studying a large corpus of\ndocuments. This paper assesses FASTREAD using datasets generated from existing\nSE literature reviews (Hall, Wahono, Radjenovi\\'c, Kitchenham et al.). Compared\nto manual methods, FASTREAD lets researchers find 95% relevant studies after\nreviewing an order of magnitude fewer papers. Compared to other\nstate-of-the-art automatic methods, FASTREAD reviews 20-50% fewer studies while\nfinding same number of relevant primary studies in a systematic literature\nreview.","url_abs":"http://arxiv.org/abs/1612.03224v5","url_pdf":"http://arxiv.org/pdf/1612.03224v5.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":"finding-better-active-learners-for-faster","repo_url":"https://github.com/fastread/src","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"active-learning","task_name":"Active Learning"},{"task_slug":"systematic-literature-review","task_name":"Systematic Literature Review"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}