A task completion framework to support single-interaction IR research

Author:

van der Vegt AntonORCID,Zuccon Guido,Koopman Bevan,Bruza Peter

Abstract

Purpose A conceptual model describes important factors within a system and how they relate to one another. They are important because they help to identify system changes that can yield the greatest improvement. Within information retrieval (IR), most research is directed towards multi-document retrieval and a multi-interaction IR user scenario. There are few, if any, IR conceptual models supporting minimal or single-interaction IR (siIR) user scenarios, however the need for siIR systems is growing rapidly. The purpose of this paper is to take the first step towards constructing a task-oriented conceptual model and experimental framework to support siIR research. Design/methodology/approach A first principles approach is employed to develop a task-oriented conceptual model, called bridging information retrieval (BIR). This model is contrasted with the concept of relevance, a central factor within IR research. Findings BIR introduces the central concept of bridging information (BI) as the objective of IR systems. BI is the additional information a user requires to complete a task, beyond their innate knowledge. The relationship between BI and relevance is determined. Research limitations/implications The theoretical basis of BIR is derived axiomatically; however the resulting system evaluation model is speculative. Practical implications The proposed operational framework offers researchers a systematic approach to designing and evaluating siIR systems. Originality/value This work contributes a novel task-oriented IR conceptual model and evaluation framework, both centred around the concept of BI for siIR. It also contributes a novel search task classification method.

Publisher

Emerald

Subject

Library and Information Sciences,Information Systems

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1. Do better search engines really equate to better clinical decisions? If not, why not?;Journal of the Association for Information Science and Technology;2020-08-18

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