Modelling Dynamic Interactions Between Relevance Dimensions

Uprety, Sagar; Dehdashti, Shahram; Fell, Lauren; Bruza, Peter and Song, Dawei (2019). Modelling Dynamic Interactions Between Relevance Dimensions. In: Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval - ICTIR '19, ACM Press pp. 35–42.



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.

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