Smart
Diary: A Smartphone-Based Framework for Sensing, Inferring, and Logging Users’
Daily Life
In this paper, we present
Smart Diary, a novel smartphone based framework that analyzes mobile sensing
data to infer, predict, and summarize people's daily activities, such as their
behavioral patterns and life styles. Such activities are then used as the basis
for knowledge representation, which generates personal digital diaries in an
automatic manner. As users do not need to intentionally participate into this
process, Smart Diary is able to make inferences and predictions based on a wide
range of information sources, such as the phones' sensor readings, locations,
and interaction history with the users, by integrating such information into a
sustainable mining model. This model is specifically developed to handle
heterogeneous and noisy sensing data, and is made to be extensible in that
users can define their own logic rules to express short-term, mid-term, and
long-term event patterns and predictions. Our evaluation results are based on
the Android platform, and they demonstrate that the Smart Diary framework can
provide accurate and easy-to-read diaries for end users without their
interventions.
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