This paper presents a supervised method for the detection and extraction of Causal Relations from open domain text. First we give a brief outline of the definition of causation an...
Questions of understanding and quantifying the representation and amount of information in organisms have become a central part of biological research, as they potentially hold th...
H. M. Aktulga, I. Kontoyiannis, L. A. Lyznik, Luka...
In this paper, we propose a general framework for real time video data mining to be applied to the raw videos (traffic videos, surveillance videos, etc.). We investigate whether t...
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
We consider here the problem of building a never-ending language learner; that is, an intelligent computer agent that runs forever and that each day must (1) extract, or read, inf...
Andrew Carlson, Justin Betteridge, Bryan Kisiel, B...