Abstract

NELL (Never-Ending Language Learner) is a computer system that runs 24/7, forever, learning to read the web and, as a result, populating and extending a Knowledge Graph. NELL has two main tasks to be performed each day: i) extract (read) more facts from the web, and integrate these into its growing knowledge graph; and ii) learn to read better than yesterday, enabling it to go back to the text it read yesterday, and today extract more facts, more accurately. This system has been running 24 hours/day for over four years now. The result so far is a knowledge graph having +90 million interconnected beliefs (e.g., servedWith(coffee, applePie), isA(applePie, bakedGood)), that NELL is considering at different levels of confidence, along with hundreds of thousands of learned phrasings, morphological features, and web page structures that NELL uses to extract beliefs from the web. The main motivation for building NELL is based on the belief that we will never really understand machine learning until we can build machines that learn many different things, over years, and become better learners over time.

Biography

Estevam R. Hruschka Jr. has received his Ph.D. degree in Computational Systems from FederalUniversity of Rio de Janeiro, Brazil, 2003. He has been ”young research fellow” at FAPESP (Sao Paulo state research agency, Brazil) and, currently, he is ”research fellow” at CNPq (Brazilian research agency). Also, he is associate professor at Federal University of Sao Carlos (UFSCar), Brazil. Professor Estevam was visiting professor (2008-2010) at Carnegie Mellon University and has been working with Professor Tom Mitchell and Professor William Cohen (at the Carnegie Mellon Read the Web project group - http://rtw.ml.cmu.edu/) since the beginning of the ReadTheWeb project (in 2008), helping to build the Never-Ending Language Learning (NELL) system that has started running on January 2010. His main research interests are never-ending learning, machine learning, probabilistic graphical models and natural language understanding. He has worked with many international research teams collaborating with research groups from universities and also from companies.