Incremental Knowledge Construction for Real-World Event Understanding | IGI Global Scientific Publishing
Welcome to the InfoSci Platform
Reference Hub4
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: © 2010 |Volume: 4 |Issue: 1 |Pages: 15
ISSN: 1557-3958|EISSN: 1557-3966|ISSN: 1557-3958|EISBN13: 9781616929312|EISSN: 1557-3966|DOI: 10.4018/jcini.2010010104
Cite Article Cite Article

MLA

Kamei, Koji, et al. "Incremental Knowledge Construction for Real-World Event Understanding." IJCINI vol.4, no.1 2010: pp.65-79. https://doi.org/10.4018/jcini.2010010104

APA

Kamei, K., Yanagisawa, Y., Maekawa, T., Kishino, Y., Sakurai, Y., & Okadome, T. (2010). Incremental Knowledge Construction for Real-World Event Understanding. International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 4(1), 65-79. https://doi.org/10.4018/jcini.2010010104

Chicago

Kamei, Koji, et al. "Incremental Knowledge Construction for Real-World Event Understanding," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI) 4, no.1: 65-79. https://doi.org/10.4018/jcini.2010010104

Export Reference

Mendeley
Favorite Full-Issue Download

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.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global Scientific Publishing bookstore.