Modeling Meaning Associated with Documental Entities: Introducing the Brussels Quantum Approach

Abstract

We show that the Brussels operational-realistic approach to quantum physics and quantum cognition offers a fundamental strategy for modeling the meaning associated with collections of documental entities. To do so, we take the World Wide Web as a paradigmatic example and emphasize the importance of distinguishing the Web, made of printed documents, from a more abstract meaning entity, which we call the Quantum Web, or QWeb, where the former is considered to be the collection of traces that can be left by the latter, in specific measurements, similarly to how a non-spatial quantum entity, like an electron, can leave localized traces of impact on a detection screen. The double-slit experiment is extensively used to illustrate the rationale of the modeling, which is guided by how physicists constructed quantum theory to describe the behavior of the microscopic entities. We also emphasize that the superposition principle and the associated interference effects are not sufficient to model all experimental probabilistic data, like those obtained by counting the relative number of documents containing certain words and co-occurrences of words. For this, additional effects, like context effects, must also be taken into consideration.

Modeling Human Decision-Making: An Overview of the Brussels Quantum Approach

“…The Brussels quantum modeling approach to conceptual entities was the starting point for the development of a quantum theoretical approach to 'meaning entities' that can be associated with documents and texts, like those of the World Wide Web, which is presented in [26].…”

“…Let us consider again the item Ashtray with respect to Home Furnishing, Furniture and Home Furnishing or Furniture. Since µ(A) + µ(B) = 0.70 + 0.30 = 1, we use the quantum formulas (26), (20) and (21), with θ d in place of θ c , to model the data. In particular, we get from (26): The quantum probability formulas ( 17) and ( 25) enable representation of most of Hampton's data on conjunctions/disjunctions of 2 concepts.…”

“…Since µ(A) + µ(B) = 0.70 + 0.30 = 1, we use the quantum formulas (26), (20) and (21), with θ d in place of θ c , to model the data. In particular, we get from (26): The quantum probability formulas ( 17) and ( 25) enable representation of most of Hampton's data on conjunctions/disjunctions of 2 concepts. We report some relevant cases in Table 1.…”

Quantum Bose-Einstein Statistics for Indistinguishable Concepts in Human Language

“…The theory explains the behavior of atoms and the particles that constitute them. The same theory is here used to explain cognitive phenomena i.e., concepts, decision making, and language by using models built from it, within a scientific discipline which has been called quantum cognition and quantum information theory (Aerts, 2009;Aerts & Beltran, 2020;Aerts et al, 2019;Aerts, Haven & Sozzo, 2018;Aerts Arguëlles, 2018;Busemeyer et al, 2011;Busemeyer & Bruza, 2011;Haven & Khrennikov, 2013;Khrennikov, 2010;Kwam et al, 2015;Melucci, 2015;Pothos & Busemeyer, 2009).…”