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Incremental Knowledge Construction for Real-World Event Understanding

Incremental Knowledge Construction for Real-World Event Understanding

Koji Kamei, Yutaka Yanagisawa, Takuya Maekawa, Yasue Kishino, Yasushi Sakurai, Takeshi Okadome
Copyright: © 2012 |Pages: 14
ISBN13: 9781466617438|ISBN10: 1466617438|EISBN13: 9781466617445
DOI: 10.4018/978-1-4666-1743-8.ch006
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MLA

Kamei, Koji, et al. "Incremental Knowledge Construction for Real-World Event Understanding." Developments in Natural Intelligence Research and Knowledge Engineering: Advancing Applications, edited by Yingxu Wang, IGI Global, 2012, pp. 83-96. https://doi.org/10.4018/978-1-4666-1743-8.ch006

APA

Kamei, K., Yanagisawa, Y., Maekawa, T., Kishino, Y., Sakurai, Y., & Okadome, T. (2012). Incremental Knowledge Construction for Real-World Event Understanding. In Y. Wang (Ed.), Developments in Natural Intelligence Research and Knowledge Engineering: Advancing Applications (pp. 83-96). IGI Global. https://doi.org/10.4018/978-1-4666-1743-8.ch006

Chicago

Kamei, Koji, et al. "Incremental Knowledge Construction for Real-World Event Understanding." In Developments in Natural Intelligence Research and Knowledge Engineering: Advancing Applications, edited by Yingxu Wang, 83-96. Hershey, PA: IGI Global, 2012. https://doi.org/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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