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Approximate Membership Localization (AML) for Web-Based Join

机译:基于Web的加入的近似成员资格本地化(AML)

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In this paper, we propose a search-based approach to join two tables in the absence of clean join attributes. Non-structured documents from the web are used to express the correlations between a given query and a reference list. To implement this approach, a major challenge we meet is how to efficiently determine the number of times and the locations of each clean reference from the reference list that is approximately mentioned in the retrieved documents. We formalize the Approximate Membership Localization (AML) problem and propose an efficient partial pruning algorithm to solve it. A study using real-word data sets demonstrates the effectiveness of our search-based approach, and the efficiency of our AML algorithm.
机译:在本文中,我们提出了一种基于搜索的方法来在没有干净联接属性的情况下联接两个表。来自网络的非结构化文档用于表达给定查询和参考列表之间的相关性。为了实现这种方法,我们遇到的主要挑战是如何有效地从检索到的文档中大约提及的参考列表中确定每个干净参考的次数和位置。我们形式化了近似成员资格本地化(AML)问题,并提出了一种有效的部分修剪算法来解决该问题。一项使用实词数据集的研究证明了我们基于搜索的方法的有效性以及我们的AML算法的效率。

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