GeoNotes: Social and Navigational Aspects of Location-Based Information Systems
UbiComp '01 Proceedings of the 3rd international conference on Ubiquitous Computing
Using GPS to learn significant locations and predict movement across multiple users
Personal and Ubiquitous Computing
Extracting places from traces of locations
Proceedings of the 2nd ACM international workshop on Wireless mobile applications and services on WLAN hotspots
Smart instant messenger in pervasive computing environments
GPC'06 Proceedings of the First international conference on Advances in Grid and Pervasive Computing
Proximity classification for mobile devices using wi-fi environment similarity
Proceedings of the first ACM international workshop on Mobile entity localization and tracking in GPS-less environments
ConaMSN: A context-aware messenger using dynamic Bayesian networks with wearable sensors
Expert Systems with Applications: An International Journal
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Location is the most essential presence information for mobile users. In this paper, we present an improved time-based clustering technique for extracting significant locations from GPS data stream. This new location extraction mechanism is incorporated with Google Maps for realizing cooperative place annotation on mobile instant messengers (MIM). To enhance the context-awareness of the MIM system, we further develop an ontology-based presence model for inferring the location clues of IM buddies. The GPS-based location extraction algorithm has been implemented on a Smartphone and evaluated using a real-life GPS trace. We show that the proposed clustering algorithm can achieve more accurate results as it considers the time interval of intermittent location revisits. The incorporation of location information with the high-level contexts, such as mobile user's current activity and their social relationship, can achieve more responsive and accurate presence update.