Reporting On Some Logic-Based Machine Reading Research

Selmer Bringsjord, Konstantine Arkoudas, Micah Clark, Andrew Shilliday, Joshua Taylor, Bettina Schimanski, Yingrui Yang

Much sponsored research in our lab either falls under or intersects with machine reading. In this short paper we give an encapsulated presentation of some of the research in question, leaving aside, for the most part, the considerable detailed technical information that underlies our work. Our machine reading research can be viewed as falling under two categories: (1)Fast, Primitive, Machine Reading in Real World Systems, and (2)Machine Reading of Diagram Infused Text. We present both in the context of our theory, Poised-For Learning by Reading.

Subjects: 10. Knowledge Acquisition; 13. Natural Language Processing

Submitted: Jan 26, 2007


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