Mining knowledge at multiple concept levels
CIKM '95 Proceedings of the fourth international conference on Information and knowledge management
Data preparation for data mining
Data preparation for data mining
Moving Objects Databases: Issues and Solutions
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
Modeling, Storing, and Mining Moving Object Databases
IDEAS '04 Proceedings of the International Database Engineering and Applications Symposium
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
Expressive power of an algebra for data mining
ACM Transactions on Database Systems (TODS)
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
Dynamic modeling of trajectory patterns using data mining and reverse engineering
ER '07 Tutorials, posters, panels and industrial contributions at the 26th international conference on Conceptual modeling - Volume 83
International Journal of Geographical Information Science
An Ontology-Based Approach for the Semantic Modelling and Reasoning on Trajectories
ER '08 Proceedings of the ER 2008 Workshops (CMLSA, ECDM, FP-UML, M2AS, RIGiM, SeCoGIS, WISM) on Advances in Conceptual Modeling: Challenges and Opportunities
A description logic approach to discover suspicious itineraries from maritime container trajectories
GeoS'11 Proceedings of the 4th international conference on GeoSpatial semantics
Mining mobility user profiles for car pooling
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
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Data mining has become very popular in the last years, and it is well known that data preprocessing is the most effort and time consuming step in the discovery process. In part, it is because database designers do not think about data mining during the conceptual design of a database, therefore data are not prepared for mining. This problem increases for spatio-temporal data generated by mobile devices, which involve both space and time. In this paper we propose a novel solution to reduce the gap between databases and data mining in the domain of trajectories of moving objects, aiming to reduce the effort for data preprocessing. We propose a general framework for modeling trajectory patterns during the conceptual design of a database. The proposed framework is a result of several works including different data mining case studies and experiments performed by the authors on trajectory data modeling and trajectory data mining. It has been validated with a data mining query language implemented in PostGIS, that allows the user to create, instantiate and query trajectory data and trajectory patterns.