Methods for discovering causal knowledge from observational data have been a persistent topic of AI research for several decades. Essentially all of this work focuses on knowledge...
Marc Maier, Brian Taylor, Huseyin Oktay, David Jen...
In this paper, we describe EventNet, a toolkit for inferring temporal relations between Commonsense events. It comprises 10,000 nodes and 30,000 temporal links mined from the Openm...
This paper proposes a novel framework called bilingual co-training for a largescale, accurate acquisition method for monolingual semantic knowledge. In this framework, we combine ...
Multi-relational networks are used extensively to structure knowledge. Perhaps the most popular instance, due to the widespread adoption of the Semantic Web, is the Resource Descr...
We present an algorithmic framework for learning multiple related tasks. Our framework exploits a form of prior knowledge that relates the output spaces of these tasks. We present...