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Spatial clustering has been widely studied due to its application in several areas. However, the algorithms of such technique still need to overcome several challenges to achieve satisfactory results on a timely basis. This work presents an algorithm for spatial clustering based on CHSMST, which allows: data clustering considering both distance and similarity, enabling to correlate spatial and nonspatial...
This work consists of the construction of a strategy called ETL-PoCon to execute Extraction, Transformation and Load (ETL) processes in active Data Warehouses (DW) with a configurable policy. The original contribution of this work is to provide a strategy that considerably reduces the quantity of data transfers to active DW, besides maintaining a satisfactory level of data freshness. Said reduction...
Spatiotemporal data stored in geographic databases provide an evolutionary panorama about the characteristics of a specific region. With integration of prediction concepts and statistical functions to that data, it is possible to make inferences of obtained information, to support in many areas such as management of occupational health, environmental resources, quality of life and, others. In this...
One way to boost the performance of a Database Management System (DBMS) is by fetching data in advance of their use, a technique known as prefetching. However, depending on the resource being used (file, disk partition, memory, etc.), the way prefetching is done might be different or even not necessary, forcing a DBMS to be aware of the underlying Storage System. In this paper we propose a Storage...
Background Once multi-relational approach has emerged as an alternative for analyzing structured data such as relational databases, since they allow applying data mining in multiple tables directly, thus avoiding expensive joining operations and semantic losses, this work proposes an algorithm with multi-relational approach. Methods Aiming to compare traditional approach performance and multi-relational...
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