Journal
MACHINE LEARNING-SCIENCE AND TECHNOLOGY
Volume 2, Issue 1, Pages -Publisher
IOP Publishing Ltd
DOI: 10.1088/2632-2153/abbd2e
Keywords
quantum computing; NLP; AI; HPC
Categories
Funding
- Enterprise Ireland
- European Union [IP 2018 0751]
- Intel
Ask authors/readers for more resources
This manuscript demonstrates the use of quantum computing models for NLP tasks, developing a hybrid workflow to process small and large scale corpus data sets, showing the efficacy of the method, and releasing the developed toolkit as an open software suite.
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available