Accession Number:

AD1040065

Title:

Never-Ending Learning for Deep Understanding of Natural Language

Descriptive Note:

Technical Report,01 Oct 2012,30 Apr 2017

Corporate Author:

Carnegie Mellon University Pittsburgh United States

Personal Author(s):

Report Date:

2017-10-01

Pagination or Media Count:

20.0

Abstract:

This research has explored the thesis that very significant amounts of background knowledge can lead to very substantial improvements in the accuracy of deep text analysis and understanding. To explore this thesis we have built on our earlier research on the Never Ending Language Learning NELL computer system, which has been running non-stop since January, 2010, learning to read the web, and automatically constructing a large knowledge base aka knowledge graph by extracting structured factual assertions from unstructured text on the web.

Subject Categories:

  • Information Science
  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE