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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. Expand
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. Expand
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. Expand
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. Expand
Closest pair queries in spatial databases
This paper addresses the problem of finding the K closest pairs between two spatial data sets, where each set is stored in a structure belonging in the R-tree family. Five different algorithms (fourExpand
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. Expand
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. Expand
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. Expand
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