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An Algorithmic Study of Deduction in Simple Conceptual Graphs with Classical Negation

机译:简单概念图与经典否定演绎的算法研究

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Polarized conceptual graphs (PGs) are simple conceptual graphs added with a restricted form of negation, namely negation on relations. Classical deduction with PGs (in short PG-Deduction) is highly intractable; it is indeed π_p~2 complete. In [LM06] a brute-force algorithm for solving PG-Deduction was outlined. In the present paper, we extend previous work with two kinds of results. First, we exhibit particular cases of PGs for which the complexity of PG-Deduction decreases and becomes not more difficult than in simple conceptual graphs. Secondly, we improve the brute-force algorithm with several kinds of techniques based on properties concerning the graph structure and the labels.
机译:极化概念图(PGs)是简单的概念图,添加了否定的受限形式,即关系否定。 PG的经典演绎(简称PG演绎)非常棘手;确实是π_p〜2完整。在[LM06]中,概述了解决PG推导的蛮力算法。在本文中,我们用两种结果扩展了以前的工作。首先,我们展示了PG的特殊情况,其PG演绎的复杂性降低了,并且变得不比简单概念图中的困难。其次,基于涉及图结构和标签的属性,我们使用多种技术改进了蛮力算法。

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