Displaying similar documents to “Supervised learning for record linkage through weighted means and OWA operators”

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...

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...

User Profiling for the Web

Miha Grčar, Dunja Mladenič, Marko Grobelnik (2006)

Computer Science and Information Systems

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On the learning of weights in some aggregation operators: the weigthed mean and OWA operators.

Vicenç Torra (1999)

Mathware and Soft Computing

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We study the determination of weights for two types of aggregation operators: the weighted mean and the OWA operator. We assume that there is at our disposal a set of examples for which the outcome of the aggregation operator is known. In the case of the OWA operator, we compare the results obtained by our method with another one in the literature. We show that the optimal weighting vector is reached with less cost.

Bringing introspection into BlobSeer: Towards a self-adaptive distributed data management system

Alexandra Carpen-Amarie, Alexandru Costan, Jing Cai, Gabriel Antoniu, Luc Bougé (2011)

International Journal of Applied Mathematics and Computer Science

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Introspection is the prerequisite of autonomic behavior, the first step towards performance improvement and resource usage optimization for large-scale distributed systems. In grid environments, the task of observing the application behavior is assigned to monitoring systems. However, most of them are designed to provide general resource information and do not consider specific information for higher-level services. More precisely, in the context of data-intensive applications, a specific...

Protecting micro-data by micro-aggregation: the experience in Eurostat.

Daniel Defays (1997)

Qüestiió

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A natural strategy to protect the confidentiality of individual data is to aggregate them at the lowest possible level. Some studies realised in Eurostat on this topic will be presented: properties of classifications in clusters of fixed sizes, micro-aggregation as a generic method to protect the confidentiality of individual data, application to the Community Innovation Survey. The work performed in Eurostat will be put in line with other projects conducted at European level on the...