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Constructing lattice based on irreducible concepts

机译:基于不可约概念构造晶格

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摘要

The construction of concept lattices is one of the key issues of formal concept analysis. Many methods and algorithms are proposed to build a lattice, among which, incremental algorithms are more appropriate in real-life applications that work with dynamic datasets. But they cost much time to locate generators before generating a real concept. The batch algorithms generate concepts quickly. However, they ignore the procedure of building lattice relationship. In this paper, we build the lattice from meet-irreducible attribute concepts by using generators directly, and make optimizations in key steps. We yield the relationship among concepts during the generating process that saves much time in contrast to other batch algorithms. In addition to proving the correctness of our algorithm, we evaluate its performance on some real datasets and compare it with an incremental algorithm called FastAddIntent. The results show that our algorithm mainly depends on the numbers of concepts and the numbers of attributes, which achieves good performance, especially to large formal contexts.
机译:概念格的构建是形式概念分析的关键问题之一。提出了许多方法和算法来构建网格,其中,增量算法更适合用于动态数据集的实际应用。但是在生成实际概念之前,它们花费大量时间来定位生成器。批处理算法可快速生成概念。但是,他们忽略了建立晶格关系的过程。在本文中,我们通过直接使用生成器,从满足不可约属性概念来构建晶格,并在关键步骤中进行了优化。与其他批处理算法相比,我们在生成过程中产生了概念之间的关系,从而节省了大量时间。除了证明我们算法的正确性之外,我们还评估了它在某些实际数据集上的性能,并将其与称为FastAddIntent的增量算法进行了比较。结果表明,我们的算法主要取决于概念的数量和属性的数量,从而取得良好的性能,特别是在大型形式环境下。

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