Abstract:

Quantum theory has the characteristics of superposition, entanglement, incompatibility, and interference, which make it an excellent modeling framework. For the purpose of sentence matching, we explore the ability of quantum theory as a framework to capture sentence meaning and model semantic processes. We use quantum states to construct the semantic Hilbert space and calculate the fidelity of information during sentence transformation. The similarity of sentences is subsequently determined by using word embedding technology to represent words or concepts in semantic vector spaces. Simulation data showed that the proposed method achieved better results than traditional methods for sentence matching datasets constructed on real business scenarios. Hence, this paper provides a new idea for similarity research of multiple sentences and introduces a breakthrough in interdisciplinary research between computer science and quantum theory, in line with current research trends.

Key words: quantum theory, natural language, fidelity, sentence similarity