J
Justin Betteridge
Researcher at Carnegie Mellon University
Publications - 14
Citations - 3508
Justin Betteridge is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Knowledge base & Information extraction. The author has an hindex of 10, co-authored 14 publications receiving 3047 citations.
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Proceedings Article
Toward an architecture for never-ending language learning
Andrew Carlson,Justin Betteridge,Bryan Kisiel,Burr Settles,Estevam R. Hruschka,Tom M. Mitchell +5 more
TL;DR: This work proposes an approach and a set of design principles for an intelligent computer agent that runs forever and describes a partial implementation of such a system that has already learned to extract a knowledge base containing over 242,000 beliefs.
Proceedings ArticleDOI
Coupled semi-supervised learning for information extraction
TL;DR: This paper characterize several ways in which the training of category and relation extractors can be coupled, and presents experimental results demonstrating significantly improved accuracy as a result.
Journal ArticleDOI
Never-ending learning
Tom M. Mitchell,William W. Cohen,Estevam R. Hruschka,Partha Pratim Talukdar,Bishan Yang,Justin Betteridge,Andrew Carlson,Bhavana Dalvi,Matt Gardner,Bryan Kisiel,Jayant Krishnamurthy,Ni Lao,Kathryn Mazaitis,T. Mohamed,Ndapandula Nakashole,Emmanouil Antonios Platanios,Alan Ritter,Mehdi Samadi,Burr Settles,Richard Wang,Derry Tanti Wijaya,Abhinav Gupta,Xinlei Chen,Abulhair Saparov,M. Greaves,J. Welling +25 more
TL;DR: The Never-Ending Language Learner (NELL) as discussed by the authors is a case study of a machine learning system that learns to read the Web 24hrs/day since January 2010, and so far has acquired a knowledge base with 120mn diverse, confidence-weighted beliefs (e.g., servedWith(tea,biscuits), while learning thousands of interrelated functions that continually improve its reading competence over time.
Proceedings Article
Never-ending learning
Tom M. Mitchell,William W. Cohen,Estevam R. Hruschka,Partha Pratim Talukdar,Justin Betteridge,Andrew Carlson,Bhavana Dalvi,Matt Gardner,Bryan Kisiel,Jayant Krishnamurthy,Ni Lao,Kathryn Mazaitis,T. Mohamed,Ndapandula Nakashole,Emmanouil Antonios Platanios,Alan Ritter,Mehdi Samadi,Burr Settles,Richard Wang,Derry Tanti Wijaya,Abhinav Gupta,Xinlei Chen,Abulhair Saparov,M. Greaves,J. Welling +24 more
TL;DR: The Never-Ending Language Learner (NELL) as discussed by the authors is a machine learning system that learns to read the web 24 hours/day since January 2010, and so far has acquired a knowledge base with over 80 million confidence-weighted beliefs (e.g., servedWith(tea, biscuits), while continuously improving its reading competence over time.
Proceedings ArticleDOI
Coupling Semi-Supervised Learning of Categories and Relations
TL;DR: Experimental results show that simultaneously learning a coupled collection of classifiers for 30 categories and relations results in much more accurate extractions than training classifiers individually.