Modelling Dynamic Interactions between Relevance Dimensions
This work addresses the challenge of understanding dynamic cognitive processes in information retrieval, offering a novel theoretical approach that could inform system design, though it appears incremental in applying quantum frameworks to this domain.
The paper tackled the problem of modeling interactions between relevance dimensions in information retrieval by using quantum theory to explain cognitive decision-making, resulting in a complex-valued vector space model that demonstrates incompatibility and interference effects.
Relevance is an underlying concept in the field of Information Science and Retrieval. It is a cognitive notion consisting of several different criteria or dimensions. Theoretical models of relevance allude to interdependence between these dimensions, where their interaction and fusion leads to the final inference of relevance. We study the interaction between the relevance dimensions using the mathematical framework of Quantum Theory. It is considered a generalised framework to model decision making under uncertainty, involving multiple perspectives and influenced by context. Specifically, we conduct a user study by constructing the cognitive analogue of a famous experiment in Quantum Physics. The data is used to construct a complex-valued vector space model of the user's cognitive state, which is used to explain incompatibility and interference between relevance dimensions. The implications of our findings to inform the design of Information Retrieval systems are also discussed.