IEEE Transactions on Computers
Composite Events for Active Databases: Semantics, Contexts and Detection
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Using GPS to learn significant locations and predict movement across multiple users
Personal and Ubiquitous Computing
BMQ-Index: Shared and Incremental Processing of Border Monitoring Queries over Data Streams
MDM '06 Proceedings of the 7th International Conference on Mobile Data Management
High-performance complex event processing over streams
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
IEEE Transactions on Knowledge and Data Engineering
Mining interesting locations and travel sequences from GPS trajectories
Proceedings of the 18th international conference on World wide web
From trajectories to activities: a spatio-temporal join approach
Proceedings of the 2009 International Workshop on Location Based Social Networks
Location-based activity recognition using relational Markov networks
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
High-performance composite event monitoring system supporting large numbers of queries and sources
Proceedings of the 5th ACM international conference on Distributed event-based system
Journal of Systems and Software
Scalable Activity-Travel Pattern Monitoring Framework for Large-Scale City Environment
IEEE Transactions on Mobile Computing
IEEE Network: The Magazine of Global Internetworking
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As location-aware mobile devices such as smartphones have now become prevalent, people are able to easily record their trajectories in daily lives. Such personal trajectories are a very promising means to share their daily life experiences, since important contextual information such as significant locations and activities can be extracted from the raw trajectories. In this paper, we propose MetroScope, a trajectory-based real-time and on-the-go experience sharing system in a metropolitan city. MetroScope allows people to share their daily life experiences through trajectories, and enables them to refer to other people's diverse and interesting experiences in a city. Eventually, MetroScope aims to satisfy users' ever-changing interest in their social environments and enrich their life experiences in a city. To achieve real-time, on-the-go, and personalized recommendation, we propose an approach of monitoring activity patterns over people's location streams.