Informing datalog through language intelligence - A personal perspective

Abstract

Despite AI's paramount aim of developing convincing similes of true natural language "understanding", crucial knowledge that is increasingly becoming available to computers in text form on web repositories remains in fact decipherable only by humans. In this position paper, we present our views on the reasons for this failure, and we argue that for bringing computers closer to becoming true extensions of the human brain, we need to endow them with a cognitively-informed web by integrating new methodologies in the inter-disciplines involved, around the pivot of Logic Programming and Datalog. © 2011 Springer-Verlag.