Keynote Talks

We describe research to develop a never-ending language learner that runs 24 hours per day, forever, and that each day has two goals. The first is to extract more information from the web to populate its growing knowledge base of structured knowledge. The second is to learn to read better than yesterday, as evidenced by its ability to go back to the same web pages it read yesterday, and extract more facts more accurately today. This research project is both a case study in how we might design an architecture for never-ending learning, and also an attempt at a new approach to natural language processing. This talk will describe our approach, and experimental results from our NELL system which has been running nonstop since January 2, 2010. As of April, it had extracted a structured knowledge base containing approximately a third of a million beliefs. You can track its progress at http://rtw.ml.cmu.edu/readtheweb.html.