Inés Fernando Vega López

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—Spatiotemporal databases are becoming increasingly more common. Typically, applications modeling spatiotemporal objects need to process vast amounts of data. In such cases, generating aggregate information from the data set is more useful than individually analyzing every entry. In this paper, we study the most relevant techniques for the evaluation of(More)
—The ability to model time-varying natures is essential to many database applications such as data warehousing and mining. However, the temporal aspects provide many unique characteristics and challenges for query processing and optimization. Among the challenges is computing temporal aggregates, which is complicated by having to compute temporal grouping.(More)
Indexing time series data is an interesting problem that has attracted much interest in the research community for the last decade. Traditional indexing methods organize the data space using different metrics. However, searching high-dimensional spaces using a hierarchical index is not always efficient because a large portion of the index might need to be(More)
The ability to model time-varying natures is essential to many database applications such as data warehous-ing and mining. However, the temporal aspects provide many unique characteristics and challenges for query processing and optimization. Among the challenges is computing temporal aggregates, which is complicated by having to compute temporal grouping.(More)
—We have developed a new indexing strategy that helps overcome the curse of dimensionality for time series data. Our proposed approach, called Skyline Index, adopts new Skyline Bounding Regions (SBR) to approximate and represent a group of time series data according to their collective shape. Skyline bounding regions allow us to define a distance function(More)
Indexing Time Series Data is an interesting problem that has attracted much interest in the research community for the last decade. Traditional indexing methods organize the data space using different metrics. For time series, however , there are some cases when a metric is not suited for properly assessing the similarity between sequences. For instance, to(More)
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