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An Efficient Relational Database Keyword Search Scheme Based on Combined Candidate Network Evaluation

机译:基于组合候选网络评估的高效关系数据库关键字搜索方案

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Relational keyword search (R-KWS) systems provide users with a convenient means in relational database queries. There exist two main types of R-KWS: those based on Data Graphs and those based on Schema Graphs. In this paper, we focus on the latter, R-KWS based on Schema Graphs. Most existing methods are typically inefficient due to the large number of repetitive operation caused by overlapping candidate networks and the execution of lots of complex queries. We present the R-KWS approach based on combined candidate network evaluation to improve the query efficiency. The proposed Combined Candidate Network (CCN) can efficiently share the overlapping part between candidate networks, and then avoid the repetitive operation during the evaluation of candidate networks. Meanwhile, CCN possesses another important characteristic that candidate networks within a CCN are still identifiable after candidate networks being compressed into a CCN. We design an algorithm based on this characteristic to evaluate CCN for the generation of final query results. This algorithm is able to eliminate the execution of a large number of complex queries required by most existing approaches, and thus significantly improve the efficiency of keyword search. Experiments on real datasets show that our approach can improve query efficiency without any loss of the quality of query results with respect to existing approaches.
机译:关系关键字搜索(R-kWs)系统为用户提供了一个方便的关系数据库查询。存在两种主要类型的R-kWs:基于数据图的那些基于模式图。在本文中,我们专注于基于模式图的后者R-KWS。由于通过重叠候选网络和大量复杂查询引起的大量重复操作,大多数现有方法通常效率低。我们基于组合候选网络评估提高查询效率的R-KWS方法。所提出的组合候选网络(CCN)可以有效地共享候选网络之间的重叠部分,然后在评估候选网络期间避免重复操作。同时,CCN具有另一个重要特征,即CCN内的候选网络仍然在被压缩到CCN中的候选网络之后仍然可识别。我们设计了一种基于此特征的算法来评估CCN的生成,用于生成最终查询结果。该算法能够消除大多数现有方法所需的大量复杂查询的执行,从而显着提高关键字搜索的效率。实际数据集的实验表明,我们的方法可以提高查询效率而不会对现有方法丢失查询结果的任何损失。

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