Toward an Architecture for Never-Ending Language Learning

We consider here the problem of building a never-ending language learner; that is, an intelligent computer agent that runs forever and that each day must (1) extract, or read, information from the web to populate a growing structured knowledge base, and (2) learn to perform this task better than on...

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Bibliographic Details
Published in:Proceedings of the ... AAAI Conference on Artificial Intelligence 2010-07, Vol.24 (1), p.1306-1313
Main Authors: Carlson, Andrew, Betteridge, Justin, Kisiel, Bryan, Settles, Burr, Hruschka, Estevam, Mitchell, Tom
Format: Article
Language:English
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Summary:We consider here the problem of building a never-ending language learner; that is, an intelligent computer agent that runs forever and that each day must (1) extract, or read, information from the web to populate a growing structured knowledge base, and (2) learn to perform this task better than on the previous day. In particular, we propose an approach and a set of design principles for such an agent, describe a partial implementation of such a system that has already learned to extract a knowledge base containing over 242,000 beliefs with an estimated precision of 74% after running for 67 days, and discuss lessons learned from this preliminary attempt to build a never-ending learning agent.
ISSN:2159-5399
2374-3468
DOI:10.1609/aaai.v24i1.7519