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NELL: a Never-Ending Language Learner system that Reads the Web

Speaker: Prof Estevam R. Hruschka Jr., Carnegie Mellon University, USA,  and Federal University of Sao Carlos (UFSCar), Brazil.


Abstract: NELL (Never-Ending Language Learner) is a computer system that runs 24/7, forever, learning to read the web. 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 base of beliefs; 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 six years now. The result so far is a collection of 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.

Prof Estevam R. Hruschka JrShort Bio:
Estevam R. Hruschka Jr. is co-leader of the Carnegie Mellon Read the Web project –http://rtw.ml.cmu.edu/rtw/), and the head of the Machine Learning Lab (MaLL) at Federal University of Sao Carlos (UFSCar), in Brazil. He is also adjunct professor in the Machine Learning Department at Carnegie Mellon University, USA, associate professor at UFSCar, Brazil and member of the AI4Good Foundation (http://ai4good.org/) Steering Committee. Estevam has been ”young research fellow” at FAPESP (Sao Paulo state research agency, Brazil) and, currently, he is ”research fellow” at CNPq (Brazilian research agency). His main research interests are never-ending learning, machine learning, probabilistic graphical models and natural language understanding. He has been working on machine learning with many international research teams, collaborating with research groups from companies and universities. 


More about the BigData@Chalmers initiative >>
Category Seminar
Location: Ledningsrummet, 2nd floor, Chalmers Student Union building (Kårhuset), Chalmersplatsen 1
Starts: 05 September, 2016, 10:30
Ends: 05 September, 2016, 12:00

Published: Thu 18 Aug 2016. Modified: Wed 24 Aug 2016