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Generating storylines from sensor data
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DOI：10.1016/j.pmcj.2013.07.005.png)
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Abstract
En 中文
We present an approach for producing narratives, or storylines, from sensor data collected from a mobile phone. Given a training set of English-language descriptions of events and a set of corresponding sensor data, we learn a probabilistic translation model. Then, given new sensor data, our model can produce English-language descriptions of the corresponding events. Our approach is evaluated on the data provided as part of the Nokia Mobile Data Challenge (MDC), focusing, in particular, on location labelling. We also present a set of tools for visualizing the MDC data, which were used to generate training data for storyline creation. Finally, we present a quantitative analysis of wifi data in a busy office setting, and present a novel model for wifi signals that more accurately matches the properties of signals in a natural environment. (C) 2013 Elsevier B.V. All rights reserved.
Keywords:
Mobile computing
Statistical machine translation
User activity summarization
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