We present a novel approach to discovering relations and their instantiations from a collection of documents in a single domain. Our approach learns relation types by exploiting m...
Harr Chen, Edward Benson, Tahira Naseem, Regina Ba...
There are many problems requiring a semantic account of a database schema. At its best, such an account consists of mapping formulas between the schema and a formal conceptual mode...
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
This workfocuses on the inference of evolutionary relationships in protein superfamilies, and the uses of these relationships to identify keypositions in the structure, to infer a...
We present a trainable sequential-inference technique for processes with large state and observation spaces and relational structure. Our method assumes "reliable observation...