Abstract
This dissertation aims to quantify the consumer experience in reality by building a real-space information based space model and consumer behavior model. We applied the models and used it to implement the simulator. The developed simulator collects the information generated in the virtual living space for the purpose of developing a smart home simulator. To predict user behavior, data is compiled from experiment panels. By using weka, features are extracted from the amassed data and the feature value’s complexity is reduced. Through optimal subsets of the feature values we could make a judgment on the accuracy of the predicted behaviors.
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Bang, G., Ko, I. (2017). A User Empirical Context Model for a Smart Home Simulator. In: Park, J., Pan, Y., Yi, G., Loia, V. (eds) Advances in Computer Science and Ubiquitous Computing. UCAWSN CUTE CSA 2016 2016 2016. Lecture Notes in Electrical Engineering, vol 421. Springer, Singapore. https://doi.org/10.1007/978-981-10-3023-9_85
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DOI: https://doi.org/10.1007/978-981-10-3023-9_85
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