Uncertain data is inherent in various important applications and Top-[Formula: see text] query on uncertain data is an important query type for many applications. To tackle the performance issue of evaluating Top-[Formula: see text] query on uncertain data, an efficient optimization approach was proposed in this paper. This method can anticipate the tuples most likely to become Top-[Formula: see text] result based on dominant relationship analysis, greatly reducing the amount of data in query processing. When the database is updated, this method could determine whether the change affects the current query result, and help us to avoid unnecessary re-query. The experimental results prove the feasibility and effectiveness of this method.

中文翻译：

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一种针对不确定数据的 Top-k 查询的有效优化方法

不确定数据是各种重要应用所固有的，Top-[公式：见正文]对不确定数据的查询是许多应用的重要查询类型。针对不确定数据评估Top-[Formula:see text]查询的性能问题，本文提出了一种有效的优化方法。该方法可以基于优势关系分析预测最有可能成为Top-[公式：见正文]结果的元组，大大减少了查询处理中的数据量。当数据库更新时，该方法可以判断更改是否影响当前查询结果，帮助我们避免不必要的重新查询。实验结果证明了该方法的可行性和有效性。