This paper describes experiments showing that some problems in natural language processing can already be addressed using quantum computers. The examples presented here include topic classification using both a quantum support vector machine and a bag-of-words approach, bigram modeling that can be applied to sequences of words and formal concepts, and ambiguity resolution in verb-noun composition. While the datasets used are still small, the systems described have been run on physical quantum computers. These implementations and their results are described along with the algorithms and mathematical approaches used.
翻译:本文介绍一些实验,表明自然语言处理中的一些问题已经可以用量子计算机来解决,这里列举的例子包括使用量子支持矢量机和一袋字的方法进行专题分类、可适用于文字序列和正式概念的重线建模以及动词名构成的模糊分辨率。虽然使用的数据集仍然很小,但所述系统是在物理量子计算机上运行的。这些实施及其结果与所使用的算法和数学方法一起描述。