Abstract-The location tracking functionality of modern mobile devices provides unprecedented opportunity to the understanding of individual mobility in daily life. Instead of studying raw geographic coordinates, we are interested in understanding human mobility patterns based on sequences of place visits which encode, at a coarse resolution, most daily activities. This paper presents a study on place characterization in people's everyday life based on data recorded continuously by smartphones. First, we study human mobility from sequences of place visits, including visiting patterns on different place categories. Second, we address the problem of automatic place labeling from smartphone data without using any geo-location information. Our study on a large-scale data collected from 114 smartphone users over 18 months confirm many intuitions, and also reveals findings regarding both regularly and novelty trends in visiting patterns. Considering the problem of place labeling with 10 place categories, we show that frequently visited places can be recognized reliably (over 80 percent) while it is much more challenging to recognize infrequent places.
In REF , the authors employed the random forests classifiers to label different places without any geo-location information.
The Places of Our Lives: Visiting Patterns and Automatic Labeling from Longitudinal Smartphone Data
IEEE Transactions on Mobile Computing
IEEE Transactions on Mobile Computing
Computer Science