Overview and Evaluation of Premise Selection Techniques for Large Theory Mathematics
Overview and Evaluation of Premise Selection Techniques for Large Theory Mathematics
复制标题
大理论数学前提选择技术概述与评价
DOI：
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发表时间：
2012
期刊：
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通讯作者：
T. Heskes
中科院分区：
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作者：
D. Kühlwein;T. V. Laarhoven;Evgeni Tsivtsivadze;J. Urban;T. Heskes
本文概述了大理论数学中最先进的前提选择技术，并介绍了新的前提选择技术。介绍、比较了几种评估指标，并在大型理论数学自动推理的背景下讨论了它们的适当性。这些方法在 MPTP2078 基准（Mizar 库的子集）上进行评估，与迄今为止的最佳方法相比，获得了 10% 的改进。
In this paper, an overview of state-of-the-art techniques for premise selection in large theory mathematics is provided, and new premise selection techniques are introduced. Several evaluation metrics are introduced, compared and their appropriateness is discussed in the context of automated reasoning in large theory mathematics. The methods are evaluated on the MPTP2078 benchmark, a subset of the Mizar library, and a 10% improvement is obtained over the best method so far.