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Complex Matrices for the Approximate Evaluation of Probabilistic Queries

机译：复杂矩阵，用于概率查询的近似评估

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摘要

This paper studies the evaluation of probabilistic SPARQL queries. The evaluation of such queries is, in principle, conceptually simple and straightforward. However, it does incur a time cost that must be taken into account. It thus expedient to devise methods that lower this cost. We propose and explain such a method, that makes use of complex matrices. The idea to resort to the complex numbers is inspired from the greatly expanding field of unconventional computing, and, in particular, from quantum computing. This novel proposal simplifies and speeds up calculation of products of probabilities. Therefore, is particularly promising in these cases where the same answer set can be obtained either by employing exact computations or by employing suitable approximations, as is indeed the case in many probabilistic queries.
机译：本文研究了概率的SPARQL查询的评估。原则上，对这些查询的评估是概念上简单和简单的。但是，它会产生必须考虑的时间成本。因此，有利的是设计降低此费用的方法。我们提出并解释了这种方法，这是利用复杂的矩阵。借助复杂数字的想法是从大常规计算的大大扩大领域的启发，并且特别是来自量子计算。这项新颖的提案简化并加快了概率产品的计算。因此，在这些情况下特别有前途，其中通过采用精确计算或通过采用合适的近似来获得相同的答案集，实际上是许多概率查询中的情况。

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