Database reverse engineering: from the relational to the binary relationship model
Data & Knowledge Engineering
GeoFrame-T: a temporal conceptual framework for data modeling
Proceedings of the 9th ACM international symposium on Advances in geographic information systems
Moving Objects Databases: Issues and Solutions
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
Efficient Mining of Spatiotemporal Patterns
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Modeling, Storing, and Mining Moving Object Databases
IDEAS '04 Proceedings of the International Database Engineering and Applications Symposium
Geoinformatica
Conceptual Modeling for Traditional and Spatio-Temporal Applications: The MADS Approach
Conceptual Modeling for Traditional and Spatio-Temporal Applications: The MADS Approach
Modeling and querying moving objects in networks
The VLDB Journal — The International Journal on Very Large Data Bases
Computing longest duration flocks in trajectory data
GIS '06 Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems
Mining frequent geographic patterns with knowledge constraints
GIS '06 Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems
Discovery of Collocation Episodes in Spatiotemporal Data
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
A model for enriching trajectories with semantic geographical information
Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems
International Journal of Geographical Information Science
DASFAA'06 Proceedings of the 11th international conference on Database Systems for Advanced Applications
A model for enriching trajectories with semantic geographical information
Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems
A conceptual view on trajectories
Data & Knowledge Engineering
A clustering-based approach for discovering interesting places in trajectories
Proceedings of the 2008 ACM symposium on Applied computing
A conceptual data model for trajectory data mining
GIScience'10 Proceedings of the 6th international conference on Geographic information science
A description logic approach to discover suspicious itineraries from maritime container trajectories
GeoS'11 Proceedings of the 4th international conference on GeoSpatial semantics
Travel time prediction using machine learning
Proceedings of the 4th ACM SIGSPATIAL International Workshop on Computational Transportation Science
A visual analytics system for metropolitan transportation
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
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The constant increase of moving object data imposes the need for modeling, processing, and mining trajectories, in order to find and understand the patterns behind these data. Existing works have mainly focused on the geometric properties of trajectories, while the semantics and the background geographic information has rarely been addressed. We claim that meaningful patterns can only be extracted from trajectories if the geographic space where trajectories are located is considered. In this paper we propose a reverse engineering framework for mining and modeling semantic trajectory patterns. Since trajectory patterns are data dependent, they may not be modeled in conceptual geographic database schemas before they are known. Therefore, we apply data mining to extract general trajectory patterns, and through a new kind of relationships, we model these patterns in the geographic database schema. A case study shows the power of the framework for modeling semantic trajectory patterns in the geographic space.