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Knowledge discovery in deductive databases with large deduction results: the first step

机译:演绎结果丰富的演绎数据库中的知识发现:第一步

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Deductive databases have the ability to deduce new facts from a set of existing facts by using a set of rules. They are also useful in the integration of artificial intelligence and databases. However, when recursive rules are involved, the number of deduced facts can become too large to be practically stored, viewed or analyzed. This seriously hinders the usefulness of deductive databases. In order to overcome this problem, we propose four methods to discover characteristic rules from a large number of deduction results without actually having to store all the deduction results. This paper presents the first step in the application of knowledge discovery techniques to deductive databases with large numbers of deduction results.
机译:演绎数据库具有使用一组规则从一组现有事实中推断出新事实的能力。它们在人工智能和数据库的集成中也很有用。但是,当涉及到递归规则时,推论事实的数量可能太大而无法实际存储,查看或分析。这严重阻碍了演绎数据库的实用性。为了克服这个问题,我们提出了四种方法,可以从大量的推论结果中发现特征规则,而不必实际存储所有推论结果。本文介绍了将知识发现技术应用于具有大量演绎结果的演绎数据库的第一步。

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