10 Quantum machine learning in natural language processing: opportunities and challenges
Umesh Kumar Lilhore, Sarita Simaiya · 2024
Quantum natural language processing (QNLP) refers to the many approaches developed within the discipline as a result of the convergence of natural language processing (NLP) and quantum computing in recent years. This multidisciplinary field involves applying quantum mechanical insights to fundamental aspects of language processing across a wide range of NLP activities. Existing methods span a broad spectrum from theoretical demonstrations of the quantum advantage to actual implementations of algorithms using quantum hardware. This work aims to do just that by bringing together, in one place, the many different methods that have been applied to the problem. Theoretical studies and practices that have been implemented on classical or quantum hardware are separated here. The categorization also takes into account the goal of each strategy. Syntax-semantic representation is an example of a general-purpose task. In this chapter, the benefits of QNLP in terms of efficiency and methodology are dissected. In addition, it explores how QNLP techniques might be utilized in place of stateof- the-art deep learning-based methodologies.