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首页> 外文会议>IEEE International Conference on Tools with Artificial Intelligence >Skyline Computation and Maintenance over Imperfect Databases: A Marginal-Points-Based Approach
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Skyline Computation and Maintenance over Imperfect Databases: A Marginal-Points-Based Approach

机译：不完美数据库的天际线计算和维护：基于边际点的方法

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In the last decade, skyline queries have attracted the interest of several researchers in the database field due to their ability to retrieve interesting objects among a large set of objects. Skyline analysis is a powerful tool in a wide spectrum of real applications including multi-criteria optimal decision making, preference answering and many applications where uncertain, imprecise and noisy data inherently exist. As large amounts of distributed data over Internet are communicated and shared, an important problem is to retrieve the global skyline from all the distributed local sites. In addition, though the skyline queries can control selection, there exist not much works that can handle skyline queries under database updates. In this paper, based on the marginal points notions, we introduce new methods to efficiently compute the global skyline from distributed local sites and over frequently updated databases. The efficiency and effectiveness of our proposal are verified by extensive experimental results.
机译：在过去的十年中，由于天际线查询具有检索大量对象中有趣的对象的能力，因此吸引了数据库领域的几位研究人员的兴趣。在许多实际应用中，天际线分析是一个强大的工具，包括多准则的最佳决策，偏好回答以及固有地存在不确定，不精确和嘈杂数据的许多应用。随着Internet上大量分布式数据的通信和共享，一个重要的问题是从所有分布式本地站点中检索全球天际线。此外，尽管天际线查询可以控制选择，但是在数据库更新下没有太多可以处理天际线查询的工作。在本文中，基于边际点的概念，我们介绍了新的方法来有效地从分布式本地站点和频繁更新的数据库中计算全球天际线。我们的建议的效率和有效性已通过广泛的实验结果得到验证。

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