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This work presents a technique of convincingly claiming ownership rights over a trajectory dataset. The presented methodology distorts imperceptibly a collection of sequences, effectively embedding a secret key, while retaining as well as possible the neighborhood of each object, which is vital for operations such as similarity search, classification or clustering.
Data cubes have become important components in most data warehouse systems and decision support systems. In such systems, users usually pose very complex queries to the online analytical processing (OLAP) system, and systems usually have to deal with a huge amount of data because of the large dimensionality of the sets; thus, approximating query processing has emerged as a viable solution. Specifically,...
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