Quantum emulation of query extension in information retrieval

TL;DR

This paper explores quantum and classical models of information retrieval using a physical measurement analogy, demonstrating that Bayesian query expansion remains effective in both frameworks for improving document relevance.

Contribution

It introduces a novel quantum emulation approach to query expansion in information retrieval, extending classical models with quantum-inspired insights.

Findings

Bayesian query expansion boosts relevance in both classical and quantum models.

Quantum emulation offers new perspectives on information retrieval processes.

Classical and quantum models show qualitative agreement in query expansion effectiveness.

Abstract

An operationalistic scheme, called Melucci metaphor, is suggested representing Information Retrieval as physical measurements with beam of particles playing the role of the flow of retrieved documents. The possibilities of query expansion by extra term are studied from this perspective, when the particles-`docuscles' are assumed to be of classical or quantum nature. It is shown that in both cases the choice of an extra term based on Bayesian belief revision is still valid on the qualitative level for boosting the relevance of the retrieved documents.