Building and Using Models of Information Seeking, Search and Retrieval

Abstract

Understanding how people interact with information systems when searching is central to the study of Interactive Information Retrieval (IIR). While much of the prior work in this area has either been conceptual, observational or empirical, recently there has been renewed interest in developing mathematical models of information seeking and search. This is because such models can provide a concise and compact representation of search behaviours and naturally generate testable hypotheses about search behaviour. This full day tutorial focuses on explaining and building formal models of Information Seeking and Retrieval. The tutorial is structured into four sessions. In the first session we will discuss the rationale of modelling and examine a number of early formal models of search (including early cost models and the Probability Ranking Principle). Then we will examine more contemporary formal models (including Information Foraging Theory, the Interactive Probability Ranking Principle, and Search Economic Theory). The focus will be on the insights and intuitions that we can glean from the math behind these models. The latter sessions will be dedicated to building models that optimise particular objectives which drive how users make decisions, along with a how-to guide on model building, where we will describe different techniques (including analytical, graphical and computational) that can be used to generate hypotheses from such models. In the final session, participants will be challenged to develop a simple model of interaction applying the techniques learnt during the day, before concluding with an overview of challenges and future directions.