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UTILIZING NATURAL LANGUAGE PROCESSING SIMILARITY MATCHING TO DETERMINE WHETHER A PROBLEM REQUIRES QUANTUM COMPUTING OR CLASSICAL COMPUTING

机译:利用自然语言处理相似性匹配以确定问题是否需要量子计算或经典计算

摘要

In some implementations, an advisor system may receive a description of a problem to be solved and problem data identifying quantum computing-related and classical computing-related problems. The advisor system may perform natural language processing on the description of the problem and the problem data to respectively generate a problem embedding vector for the problem and to generate embedding vectors that represent the quantum computing-related and classical computing-related problems. The advisor system may process the problem embedding vector and the embedding vectors, with a vector matching model, to determine a semantically closest matching one of the embedding vectors to the problem embedding vector and, accordingly, may generate a recommendation that includes an indication to solve the problem with a classical computing resource, a quantum computing resource, or a combination of a classical computing resource and a quantum computing resource.
机译:在一些实施方式中,顾问系统可以接收要解决的问题的描述和识别昆腾计算相关和经典计算相关问题的问题数据。顾问系统可以对问题的描述进行自然语言处理,并且问题数据分别为问题的嵌入向量生成问题,并生成代表与量子计算相关和古典计算相关问题的嵌入向量。顾问系统可以处理嵌入向量和嵌入向量的问题匹配模型,以确定嵌入媒体嵌入矢量的嵌入向量之一的语义上最近的匹配,并且相应地可以生成包括要解决的指示的推荐具有经典计算资源的问题,量子计算资源或经典计算资源和量子计算资源的组合。

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