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Incremental Knowledge Construction for Real-World Event Understanding
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Author(s): Koji Kamei (ATR Intelligent Robotics and Communication Laboratories, Japan), Yutaka Yanagisawa (NTT Communication Science Laboratories, Japan), Takuya Maekawa (NTT Communication Science Laboratories, Japan), Yasue Kishino (NTT Communication Science Laboratories, Japan), Yasushi Sakurai (NTT Communication Science Laboratories, Japan)and Takeshi Okadome (Kwansei Gakuin University, Japan)
Copyright: 2012
Pages: 14
Source title:
Developments in Natural Intelligence Research and Knowledge Engineering: Advancing Applications
Source Author(s)/Editor(s): Yingxu Wang (University of Calgary, Canada)
DOI: 10.4018/978-1-4666-1743-8.ch006
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Abstract
The construction of real-world knowledge is required if we are to understand real-world events that occur in a networked sensor environment. Since it is difficult to select suitable ‘events’ for recognition in a sensor environment a priori, we propose an incremental model for constructing real-world knowledge. Labeling is the central plank of the proposed model because the model simultaneously improves both the ontology of real-world events and the implementation of a sensor system based on a manually labeled event corpus. A labeling tool is developed in accordance with the model and is evaluated in a practical labeling experiment.
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