We present a novel ensemble architecture for learning problem-solving techniques from a very small number of expert solutions and demonstrate its effectiveness in a complex real-world domain.
Inferring logical consequences from a set of asserted facts or axioms.
We present a prototype web service that enables researchers to evaluate the performance per watt of semantic web tools. The web service provides access to a hardware platform for collecting power consumption data for a mobile device.
We introduce a new methodology for benchmarking the performance per watt of semantic web reasoners and rule engines on smartphones to provide developers with information critical for deploying semantic web tools on power-constrained devices.
The proliferation of recipes and other food information on the Web presents an opportunity for discovering and organizing diet-related knowledge into a knowledge graph.
Commonsense knowledge is essential for many AI applications, including those in natural language processing, visual processing, and planning. Consequently, many sources that include commonsense knowledge have been designed and constructed over the past decades.