Web: http://arxiv.org/abs/2202.02629

Sept. 28, 2022, 1:16 a.m. | Mitchell Bosley, Saki Kuzushima, Ted Enamorado, Yuki Shiraito

cs.CL updates on arXiv.org arxiv.org

Social scientists often classify text documents to use the resulting labels
as an outcome or a predictor in empirical research. Automated text
classification has become a standard tool, since it requires less human coding.
However, scholars still need many human-labeled documents to train automated
classifiers. To reduce labeling costs, we propose a new algorithm for text
classification that combines a probabilistic model with active learning. The
probabilistic model uses both labeled and unlabeled data, and active learning
concentrates labeling efforts …

active learning arxiv classification text text classification

More from arxiv.org / cs.CL updates on arXiv.org

DATA ANALYST /- CONTROLE DE GESTION ET FINANCE H/F

@ METRO/MAKRO | Nanterre, France

Data Analyst

@ Netcentric | Barcelona, Spain

Power BI Developer

@ Lendi Group | Sydney, Australia

Staff Data Scientist - Merchant Services (Remote, North America)

@ Shopify | Dallas, TX, United States

Machine Learning / Data Engineer

@ WATI | Vietnam - Remote

F/H Data Manager

@ Bosch Group | Saint-Ouen-sur-Seine, France

[Fixed-term contract until July 2023] Data Quality Controller - Space Industry Luxembourg (m/f/o)

@ LuxSpace Sarl | Betzdorf, Luxembourg

Senior Data Engineer (Azure DataBricks/datalake)

@ SpectraMedix | East Windsor, NJ, United States

Abschlussarbeit im Bereich Data Analytics (w/m/div.)

@ Bosch Group | Rülzheim, Germany

Data Engineer - Marketing

@ Publicis Groupe | London, United Kingdom

Data Engineer (Consulting division)

@ Starschema | Budapest, Hungary

Team Leader, Master Data Management - Support CN, HK & TW

@ Publicis Groupe | Kuala Lumpur, Malaysia