Facebook Twitter LinkedIn Whatsapp iTrust Seminar Series: Transforming Big Data Into Smart Data by Dr AMit Sheth 03 Mar 2015 10.00am to 11.00am SUTD, 8 Somapah Road, Think Tank 11 (1.503), Building 1, Level 5 Abstract We will never really understand learning until we can build machines that learn many different things, over years, and become better learners over time. We describe our research to build a Never-Ending Language Learner (NELL) that runs 24 hours per day, forever, learning to read the web. Each day NELL extracts (reads) more facts from the web, into its growing knowledge base of beliefs. Each day NELL also learns to read better than the day before. NELL has been running 24 hours/day for over four years now. The result so far is a collection of 70 million interconnected beliefs (e.g., servedWtih(coffee, applePie)), NELL is considering at different levels of confidence, along with millions of learned phrasings, morphological features, and web page structures that NELL uses to extract beliefs from the web. NELL is also learning to reason over its extracted knowledge, and to automatically extend its ontology. Track NELL's progress at http://rtw.ml.cmu.edu, or follow it on Twitter at @CMUNELL. Speaker Bio Amit Sheth is an Educator, Researcher and Entrepreneur. He is the LexisNexis Ohio Eminent Scholar, an IEEE Fellow, and the executive director of Kno.e.sis-the Ohio Center of Excellence in Knowledge-enabled Computing. Kno.e.sis is a multidisciplinary Ohio Center of Excellence in BioHealth Innovation involving computer scientists, cognitive scientists, biomedical researchers and extensive clinical collaborations. It has the largest US academic research group in the area of Semantic Web. It also maintains a very high publication impact; in World Wide Web (WWW) in recent years, sharing 2nd place among universities in the world for 5-yr impact (http://j.mp/www-Mar13) and placing among the top 10 universities in the world based on 10-yr impact (http://j.mp/www-Jun14).