Displaying similar documents to “Protecting micro-data by micro-aggregation: the experience in Eurostat.”

Survival analysis on data streams: Analyzing temporal events in dynamically changing environments

Ammar Shaker, Eyke Hüllermeier (2014)

International Journal of Applied Mathematics and Computer Science

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In this paper, we introduce a method for survival analysis on data streams. Survival analysis (also known as event history analysis) is an established statistical method for the study of temporal “events” or, more specifically, questions regarding the temporal distribution of the occurrence of events and their dependence on covariates of the data sources. To make this method applicable in the setting of data streams, we propose an adaptive variant of a model that is closely related to...

Statistical databases: the reference environment and three layers proposed by Eurostat.

Roger Dubois (1997)

Qüestiió

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The functions of the Eurostat information system are divided into four sectors which correspond to the various stages in the processing of data from their collection to their difussion: - Production: collection, validation and storage of the data and meta-data; - Storage of the reference data (acceptance of the information); - Use of the reference data (visibility/security and find/deliver); - Diffusion. The system of acquisition...

Data mining techniques using decision tree model in materialised projection and selection view.

Y. W. Teh (2004)

Mathware and Soft Computing

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With the availability of very large data storage today, redundant data structures are no longer a big issue. However, an intelligent way of managing materialised projection and selection views that can lead to fast access of data is the central issue dealt with in this paper. A set of implementation steps for the data warehouse administrators or decision makers to improve the response time of queries is also defined. The study concludes that both attributes and tuples, are important...

A Taxonomy of Big Data for Optimal Predictive Machine Learning and Data Mining

Fokoue, Ernest (2014)

Serdica Journal of Computing

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Big data comes in various ways, types, shapes, forms and sizes. Indeed, almost all areas of science, technology, medicine, public health, economics, business, linguistics and social science are bombarded by ever increasing flows of data begging to be analyzed efficiently and effectively. In this paper, we propose a rough idea of a possible taxonomy of big data, along with some of the most commonly used tools for handling each particular category of bigness. The dimensionality p of...

Clustering of Symbolic Data based on Affinity Coefficient: Application to a Real Data Set

Áurea Sousa, Helena Bacelar-Nicolau, Fernando C. Nicolau, Osvaldo Silva (2013)

Biometrical Letters

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In this paper, we illustrate an application of Ascendant Hierarchical Cluster Analysis (AHCA) to complex data taken from the literature (interval data), based on the standardized weighted generalized affinity coefficient, by the method of Wald and Wolfowitz. The probabilistic aggregation criteria used belong to a parametric family of methods under the probabilistic approach of AHCA, named VL methodology. Finally, we compare the results achieved using our approach with those obtained...