Re-place-ing space: the roles of place and space in collaborative systems
CSCW '96 Proceedings of the 1996 ACM conference on Computer supported cooperative work
Using GPS to learn significant locations and predict movement across multiple users
Personal and Ubiquitous Computing
Using context-aware computing to reduce the perceived burden of interruptions from mobile devices
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Extracting places from traces of locations
ACM SIGMOBILE Mobile Computing and Communications Review
Extracting Places and Activities from GPS Traces Using Hierarchical Conditional Random Fields
International Journal of Robotics Research
EnTracked: energy-efficient robust position tracking for mobile devices
Proceedings of the 7th international conference on Mobile systems, applications, and services
Improving Location Fingerprinting through Motion Detection and Asynchronous Interval Labeling
LoCA '09 Proceedings of the 4th International Symposium on Location and Context Awareness
Discovering semantically meaningful places from pervasive RF-beacons
Proceedings of the 11th international conference on Ubiquitous computing
Using mobile phones to determine transportation modes
ACM Transactions on Sensor Networks (TOSN)
SensLoc: sensing everyday places and paths using less energy
Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems
Discovering human places of interest from multimodal mobile phone data
Proceedings of the 9th International Conference on Mobile and Ubiquitous Multimedia
Employing user feedback for semantic location services
Proceedings of the 13th international conference on Ubiquitous computing
Learning and recognizing the places we go
UbiComp'05 Proceedings of the 7th international conference on Ubiquitous Computing
Place-Its: a study of location-based reminders on mobile phones
UbiComp'05 Proceedings of the 7th international conference on Ubiquitous Computing
Simulating user intervention for interactive semantic place recognition with mobile devices
Proceedings of the 2012 RecSys workshop on Personalizing the local mobile experience
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Due to their ubiquity and ever-increasing technical capabilities, mobile devices are often used as data collection tools by researchers in multiple fields, notably HCI and Ubicomp. Although the data gathered by mobile devices can be generated from sources such as the device users, it is difficult for researchers to capture ground truth and verify data integrity beyond controlled laboratory studies. This lack of knowledge about data integrity may, in turn, affect the quality of higher-level inferences made using the data. In this paper, we report on the experience and results of a hybrid laboratory/field study in which we use mobile devices to infer the moment at which users transition between self-defined semantically meaningful personal places. The results show that filtered device motion does appear to reflect these moments of transition well, but the nature of the research question makes verification difficult in a field study.