Efficient Retrieval of Similar Time Sequences Under Time Warping
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Analyzing Relative Motion within Groups of Trackable Moving Point Objects
GIScience '02 Proceedings of the Second International Conference on Geographic Information Science
On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration
Data Mining and Knowledge Discovery
Discovering Similar Multidimensional Trajectories
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Robust and fast similarity search for moving object trajectories
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Fast time series classification using numerosity reduction
ICML '06 Proceedings of the 23rd international conference on Machine learning
On the marriage of Lp-norms and edit distance
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Mining significant graph patterns by leap search
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Discovery of convoys in trajectory databases
Proceedings of the VLDB Endowment
Proceedings of the VLDB Endowment
Mining user similarity based on location history
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
Classification of software behaviors for failure detection: a discriminative pattern mining approach
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Time series shapelets: a new primitive for data mining
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Exploiting social interactions in mobile systems
UbiComp '07 Proceedings of the 9th international conference on Ubiquitous computing
Bridging the gap between physical location and online social networks
Proceedings of the 12th ACM international conference on Ubiquitous computing
Finding similar users using category-based location history
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Swarm: mining relaxed temporal moving object clusters
Proceedings of the VLDB Endowment
On discovering moving clusters in spatio-temporal data
SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
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Spatio-temporal data collected from GPS have become an important resource to study the relationships of moving objects. While previous studies focus on mining objects being together for a long time, discovering real-world relationships, such as friends or colleagues in human trajectory data, is a fundamentally different challenge. For example, it is possible that two individuals are friends but do not spend a lot of time being together every day. However, spending just one or two hours together at a location away from work on a Saturday night could be a strong indicator of friend relationship. Based on the above observations, in this paper we aim to analyze and detect semantically meaningful relationships in a supervised way. That is, with an interested relationship in mind, a user can label some object pairs with and without such relationship. From labeled pairs, we will learn what time intervals are the most important ones in order to characterize this relationship. These significant time intervals, namely T-Motifs, are then used to discover relationships hidden in the unlabeled moving object pairs. While the search for T-Motifs could be time-consuming, we design two speed-up strategies to efficiently extract T-Motifs. We use both real and synthetic datasets to demonstrate the effectiveness and efficiency of our method.