Labeling-based knowledge construction for real-world event understanding

A sensor networked environment is capable of observing real-world phenomena as sensor readings, however, there are difficulties in understanding real-world dasiaeventspsila such as activities of daily life occurring in the environment. We propose an incremental model for constructing real-world know...

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Bibliographic Details
Main Authors: Kamei, K., Yanagisawa, Y., Maekawa, T., Kishino, Y., Sakurai, Y., Okadome, T.
Format: Conference Proceeding
Language:English
Subjects:
activities of daily life
Artificial intelligence
Cognition
Cognitive science
Computational modeling
event detection
event ontology
Humans
Information processing
Intelligent sensors
labeling
Machine intelligence
Problem-solving
Psychology
Sensor networked environment
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Description
Summary:A sensor networked environment is capable of observing real-world phenomena as sensor readings, however, there are difficulties in understanding real-world dasiaeventspsila such as activities of daily life occurring in the environment. We propose an incremental model for constructing real-world knowledge to allow us to understand real-world events. The central plank of the proposed model is the labeling practice. In the model, both the ontology of real-world events and the implementation of a sensor system are simultaneously improved based on a manually labeled event corpus. A labeling tool is developed in accordance with the model and event vocabularies are evaluated in a practical labeling experiment.
DOI:10.1109/COGINF.2009.5250792