Schema matching is a complex process focusing on matching between concepts describing the data in heterogeneous data sources. There is a shift from manual schema matching, done by...
The ways in which an agent’s actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This paper addresses the problem of ...
Ashwin Deshpande, Brian Milch, Luke S. Zettlemoyer...
This paper studies two types of spatial relationships that can be learned from training examples for object recognition. The first one employs deformable relationships between obj...
A minimally supervised machine learning framework is described for extracting relations of various complexity. Bootstrapping starts from a small set of n-ary relation instances as...
In this paper, an easily implemented semi-supervised graph learning method is presented for dimensionality reduction and clustering, using the most of prior knowledge from limited...