@inproceedings{b85a78207fa84ffa9368a400720d91db,
title = "Quantum-Like Structure in Multidimensional Relevance Judgements",
abstract = "A large number of studies in cognitive science have revealed that probabilistic outcomes of certain human decisions do not agree with the axioms of classical probability theory. The field of Quantum Cognition provides an alternative probabilistic model to explain such paradoxical findings. It posits that cognitive systems have an underlying quantum-like structure, especially in decision-making under uncertainty. In this paper, we hypothesise that relevance judgement, being a multidimensional, cognitive concept, can be used to probe the quantum-like structure for modelling users{\textquoteright} cognitive states in information seeking. Extending from an experiment protocol inspired by the Stern-Gerlach experiment in Quantum Physics, we design a crowd-sourced user study to show violation of the Kolmogorovian probability axioms as a proof of the quantum-like structure, and provide a comparison between a quantum probabilistic model and a Bayesian model for predictions of relevance.",
keywords = "Multidimensional relevance, Quantum Cognition, User behaviour",
author = "Sagar Uprety and Prayag Tiwari and Shahram Dehdashti and Lauren Fell and Dawei Song and Peter Bruza and Massimo Melucci",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 42nd European Conference on IR Research, ECIR 2020 ; Conference date: 14-04-2020 Through 17-04-2020",
year = "2020",
doi = "10.1007/978-3-030-45439-5_48",
language = "English",
isbn = "9783030454388",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "728--742",
editor = "Jose, {Joemon M.} and Emine Yilmaz and Jo{\~a}o Magalh{\~a}es and Fl{\'a}vio Martins and Pablo Castells and Nicola Ferro and Silva, {M{\'a}rio J.}",
booktitle = "Advances in Information Retrieval - 42nd European Conference on IR Research, ECIR 2020, Proceedings",
address = "Germany",
}