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On indexing evidential data

机译:关于索引证据数据

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Efficient access to data is an attractive topic because of the huge volume of nowadays information. In case of uncertain data, the issue becomes more challenging, since such data are more complex. A main technique for efficient data access is to use indexes. In this paper, we tackle the problem of indexing imperfect structured data where imperfection is managed through the Evidence theory; a generalization of the Bayesian theory. Existing data structures are presented and improved and new structures are introduced. In addition, the methods for constructing and searching data using these structured are presented. To evaluate the efficiency of the presented indexes, we implemented them and conducted extensive experiments on both synthetic and real evidential databases. A final discussion on the results shows on which criteria indexing performances depend. (C) 2019 Elsevier Inc. All rights reserved.
机译:由于当今信息量巨大,有效访问数据是一个有吸引力的话题。在数据不确定的情况下,此问题变得更具挑战性,因为此类数据更加复杂。有效数据访问的主要技术是使用索引。在本文中,我们解决了索引不完整的结构化数据的问题,该问题通过证据理论来管理不完整;贝叶斯理论的概括。提出并改进了现有的数据结构,并引入了新的结构。此外,还介绍了使用这些结构来构造和搜索数据的方法。为了评估提出的索引的效率,我们实施了它们,并在综合和真实证据数据库上进行了广泛的实验。对结果的最终讨论显示了索引性能取决于哪些标准。 (C)2019 Elsevier Inc.保留所有权利。

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