Show Student Project Statistical Learning and Refinement of RelEx Graph Transformation Rules for OpenCog sponsored by the Singularity Institute for Artificial Intelligence

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Release 0-6-20091207

Student Name:	siva reddy
Mentor Name:	Linas Vepstas
Title:	Statistical Learning and Refinement of RelEx Graph Transformation Rules
Abstract:	RelEx, a component of OpenCog, is a semantic relationship extractor. Each incoming sentence to RelEx is represented as a graph. The main engine of RelEx transforms this graph in an incremental fashion using the rules. The current graph transformation rules are hand-generated. Hand building such rules takes lot of man power, money and time. Here we present a plausible approach to learn and refine these rules automatically using corpus statistics.