.png){kind=icon}
.png){kind=icon}
Return
A hybrid classical-quantum workflow for natural language processing
.png){kind=icon}
OA
AI
DOI：10.1088/2632-2153/abbd2e.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Natural language processing (NLP) problems are ubiquitous in classical computing, where they often require significant computational resources to infer sentence meanings. With the appearance of quantum computing hardware and simulators, it is worth developing methods to examine such problems on these platforms. In this manuscript we demonstrate the use of quantum computing models to perform NLP tasks, where we represent corpus meanings, and perform comparisons between sentences of a given structure. We develop a hybrid workflow for representing small and large scale corpus data sets to be encoded, processed, and decoded using a quantum circuit model. In addition, we provide our results showing the efficacy of the method, and release our developed toolkit as an open software suite.
Keywords:
quantum computing
NLP
AI
HPC
Journal
M
IF:
4.6
Papers:
1.1K
Citations:
3.4K