Incremental Knowledge Construction for Real-World Event Understanding

Authors:
Koji Kamei;Yutaka Yanagisawa;Takuya Maekawa;Yasue Kishino;Yasushi Sakurai;Takeshi Okadome
Affiliations:
ATR Intelligent Robotics and Communication Laboratories, Japan;NTT Communication Science Laboratories, Japan;NTT Communication Science Laboratories, Japan;NTT Communication Science Laboratories, Japan;NTT Communication Science Laboratories, Japan;Kwansei Gakuin University, Japan
Venue:
International Journal of Cognitive Informatics and Natural Intelligence
Year:
2010

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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.