This paper proposes a novel hierarchical learning strategy to deal with the data sparseness problem in relation extraction by modeling the commonality among related classes. For e...
We present a weakly supervised approach to automatic Ontology Population from text and compare it with other two unsupervised approaches. In our experiments we populate a part of ...
Restricted Boltzmann Machines (RBMs) are a type of probability model over the Boolean cube {-1, 1}n that have recently received much attention. We establish the intractability of ...
In this paper, we present methods to analyze dialog coherence that help us to automatically distinguish between coherent and incoherent conversations. We build a machine learning ...
Background: The aim of this study was to provide a framework for the analysis of visceral obesity and its determinants in women, where complex inter-relationships are observed amo...