Using Linked Data for Semi-Automatic Guesstimation
Abourbih, Jonathan Alexander (University of Edinburgh) | Bundy, Alan (University of Edinburgh) | McNeill, Fiona (University of Edinburgh)
GORT is a system that combines Linked Data from across several Semantic Web data sources to solve guesstimation problems, with user assistance. The system uses customised inference rules over the relationships in the OpenCyc ontology, combined with data from DBPedia, to reason and perform its calculations. The system is extensible with new Linked Data, as it becomes available, and is capable of answering a small range of guesstimation questions.
Mar-22-2010
- Country:
- Asia > Middle East
- Israel (0.04)
- Europe
- Netherlands > North Holland
- Amsterdam (0.04)
- United Kingdom
- England (0.04)
- Scotland > City of Edinburgh
- Edinburgh (0.04)
- Netherlands > North Holland
- North America
- Canada (0.04)
- United States
- California
- Los Angeles County > Los Angeles (0.04)
- San Mateo County > Menlo Park (0.04)
- Santa Clara County > Palo Alto (0.04)
- New Jersey
- Mercer County > Princeton (0.04)
- Morris County > Parsippany (0.04)
- New York (0.04)
- California
- Asia > Middle East
- Technology: