Speaker William Cohen
Affiliation Carnegie Mellon University
Host Rich Caruana
Date recorded 12 July 2013
Carnegie Mellon University's "Never Ending Language Learner" (NELL) has been running for over three years, and has automatically extracted from the web millions of facts concerning hundreds of thousands of entities and thousands of concepts. NELL works by coupling together many interrelated large-scale semi-supervised learning problems. In this talk I will discuss some of the technical problems we encountered in building NELL, and some of the issues involved in reasoning with this sort of large, diverse, and imperfect knowledge base. This is joint work with Tom Mitchell, Ni Lao, William Wang, and many other colleagues.
©2013 Microsoft Corporation. All rights reserved.
People also watched
Bridging Software Engineering Economics and Digital Business Strategy: A Design Capital and Design Moves Perspective on Managing Software Products