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State-of-the-art in privacy preserving data mining
TLDR
An overview of the new and rapidly emerging research area of privacy preserving data mining is provided, and a classification hierarchy that sets the basis for analyzing the work which has been performed in this context is proposed.
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MONIC: modeling and monitoring cluster transitions
TLDR
This work proposes the framework MONIC for modeling and tracking of cluster transitions, which encompasses changes that involve more than one cluster, thus allowing for insights on cluster change in the whole clustering.
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Novel Approaches in Query Processing for Moving Object Trajectories
Novel Approaches to the Indexing of Moving Object Trajectories
TLDR
This work introduces two access methods for accessing trajectories of moving point objects, namely the Spatio-Temporal R-tree (STR-tree) and the Trajectory-Bundle tree (TB-tree), and presents guidelines for a successful choice among them.
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Spatio-temporal indexing for large multimedia applications
TLDR
This paper presents several spatial, temporal and spatio-temporal relationships of interest, and proposes efficient indexing schemes, based on multidimensional (spatial) data structures, for large multimedia applications that involve thousands of objects.
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Closest pair queries in spatial databases
TLDR
An extensive study based on experiments performed with synthetic as well as with real point data sets, a wide range of values for the basic parameters affecting the performance of the algorithms, especially the effect of overlap between the two data sets are explored.
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Semantic trajectories modeling and analysis
TLDR
A survey of the approaches and techniques for constructing trajectories from movement tracks, enriching trajectories with semantic information to enable the desired interpretations of movements, and using data mining to analyze semantic trajectories to extract knowledge about their characteristics.
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A model for the prediction of R-tree performance
TLDR
An analytical model that predicts the performance of R-trees (and its variants) when a range query needs to be answered and constitutes a useful tool for spatial query optimizers that need to evaluate the cost of a complex spatial query and its execution procedure.
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On the Generation of Spatiotemporal Datasets
TLDR
An algorithm, called "Generate_Spatio_Temporal_Data" (GSTD), which generates sets of moving point or rectangular data that follow an extended set of distributions is proposed, and some actual generated datasets are presented.
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Index-based Most Similar Trajectory Search
TLDR
This work defines a similarity metric, proposes an efficient approximation method to reduce its calculation cost, and develops novel metrics and heuristics to support k-most-similar-trajectory search in spatiotemporal databases exploiting on existing R-tree-like structures that are already found there to support more traditional queries.
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