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Development of a Graphics Ontology for Natural Language InterfacesNiknam, Mehdi 13 October 2010 (has links)
The overall context of this thesis research is to explore natural language as a medium to interact with computer software in the graphics domain, e.g. programs like MS Paint or OpenGL. A core element of most natural language understanding systems is an ontology, which represents concepts and items of the underlying domain of discourse. This thesis presents an ontology for the graphics domain based on several resources, including documentation and textbooks on graphics systems, existing ontologies, and - most importantly - a collection of natural language instructions to create and modify graphic images. The ontology was developed in several phases, and finally tested as part of a complex natural language interface. This natural language interface accepts verbal instructions in the graphics domain as input and creates matching graphic images as output. The results of our tests indicate an accuracy of the system in the area of 80%.
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Development of a Graphics Ontology for Natural Language InterfacesNiknam, Mehdi 13 October 2010 (has links)
The overall context of this thesis research is to explore natural language as a medium to interact with computer software in the graphics domain, e.g. programs like MS Paint or OpenGL. A core element of most natural language understanding systems is an ontology, which represents concepts and items of the underlying domain of discourse. This thesis presents an ontology for the graphics domain based on several resources, including documentation and textbooks on graphics systems, existing ontologies, and - most importantly - a collection of natural language instructions to create and modify graphic images. The ontology was developed in several phases, and finally tested as part of a complex natural language interface. This natural language interface accepts verbal instructions in the graphics domain as input and creates matching graphic images as output. The results of our tests indicate an accuracy of the system in the area of 80%.
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