Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Similarity-based queries for time series data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Supporting fast search in time series for movement patterns in multiple scales
Proceedings of the seventh international conference on Information and knowledge management
Motion-Based Recognition
Time Granularities in Databases, Data Mining and Temporal Reasoning
Time Granularities in Databases, Data Mining and Temporal Reasoning
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
Approximate Queries and Representations for Large Data Sequences
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
On Similarity Queries for Time-Series Data: Constraint Specification and Implementation
CP '95 Proceedings of the First International Conference on Principles and Practice of Constraint Programming
Efficient Similarity Search over Future Stream Time Series
IEEE Transactions on Knowledge and Data Engineering
Motion-Alert: automatic anomaly detection in massive moving objects
ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
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An important investigation of moving objects involves searching for objects with specific movement patterns, such as "going up," "going towards southwest," or a combination of these. Movement patterns can be in various scales, and larger-scale patterns usually span over longer time periods with greater disturbances ignored. Movement pattern queries ask for moving objects which show a given movement pattern in a specific scale. This paper studies database techniques to support fast evaluation of movement pattern queries in user-specified scales. The database is assumed to contain position information of moving objects sampled at a certain time interval. A movement pattern is defined as a regular expression of movement letters where each letter describes a set of movement directions. For each series of positions, movement directions of all scales are precomputed and results are mapped into points on a plane. Points on this plane usually cluster well and can be readily bounded by trapezoids. These bounding trapezoids are then stored in a relational database and the query language SQL can be used to help evaluate movement pattern queries. This paper also reports some experiments conducted on a real data set as well as a synthesized data set. Results show that both the precomputation algorithm and the bounding strategy are efficient and scalable.