Quantum Text Encoding for Classification Tasks
Quantum Physics
2023-01-11 v1
Abstract
This paper explores text classification on quantum computers. Previous results have achieved perfect accuracy on an artificial dataset of 100 short sentences, but at the unscalable cost of using a qubit for each word. This paper demonstrates that an amplitude encoded feature map combined with a quantum support vector machine can achieve 62% average accuracy predicting sentiment using a dataset of 50 actual movie reviews. This is still small, but considerably larger than previously-reported results in quantum NLP.
Cite
@article{arxiv.2301.03715,
title = {Quantum Text Encoding for Classification Tasks},
author = {Aaranya Alexander and Dominic Widdows},
journal= {arXiv preprint arXiv:2301.03715},
year = {2023}
}