Interactive information retrieval

Ruthven, Ian

doi:10.1002/aris.2008.1440420109

Cited by 83 publications

(71 citation statements)

References 194 publications

(175 reference statements)

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“…Mental and physical costs have been incorporated into evaluation measures as fixed parameters (for example, by introducing discounting based on rank [24]) and used to characterize interactions [25], but they have rarely been studied as independent variables because they are difficult to manipulate and measure. While many interactive search studies incorporate effort-based measures, such as the number of documents examined, number of queries issued and amount of time spent performing different actions [35,25], few studies have attempted to model how interaction costs shape search behavior [27]. There have been some exceptions, though, where information seeking and retrieval behavior has been formally modeled using a cost-benefit framework [2,31,34].…”

Section: Introductionmentioning

confidence: 99%

How query cost affects search behavior

Azzopardi

Kelly

Brennan

2013

Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval

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We investigate how the cost associated with querying in the context of information retrieval affects how users interact with a search system. Microeconomic theory is used to generate the cost-interaction hypothesis that states as the cost of querying increases, users will pose fewer queries and examine more documents per query. A between-subjects laboratory study with 36 undergraduate subjects was conducted, where subjects were randomly assigned to use one of three search interfaces that varied according to the amount of physical cost required to query: Structured (high cost), Standard (medium cost) and Query Suggestion (low cost). Results show that subjects who used the Structured interface submitted significantly fewer queries, spent more time on search results pages, examined significantly more documents per query, and went to greater depths in the search results list. Results also showed that these subjects spent longer generating their initial queries, saved more relevant documents and rated their queries as more successful. These findings have implications for the usefulness of microeconomic theory as a way to model and explain search interaction, as well as for the design of query facilities.

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Section: Introductionmentioning

confidence: 99%

How query cost affects search behavior

Azzopardi

Kelly

Brennan

2013

Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval

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“…Often the user will need to pose a number of queries and examine numerous documents before their underlying information need is satisfied [6,18]. Given that searching for information requires user effort (and thus a cost), it is interesting to consider what kinds of search strategies a user could or should employ to efficiently undertake their search task.…”

Section: Introductionmentioning

confidence: 99%

The economics in interactive information retrieval

Azzopardi

2011

Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval

112

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Searching is inherently an interactive process usually requiring numerous iterations of querying and assessing in order to find the desired amount of relevant information. Essentially, the search process can be viewed as a combination of inputs (queries and assessments) which are used to "produce" output (relevance). Under this view, it is possible to adapt microeconomic theory to analyze and understand the dynamics of Interactive Information Retrieval. In this paper, we treat the search process as an economics problem and conduct extensive simulations on TREC test collections analyzing various combinations of inputs in the "production" of relevance. The analysis reveals that the total Cumulative Gain obtained during the course of a search session is functionally related to querying and assessing. Furthermore, this relationship can be characterized mathematically by the Cobbs-Douglas production function. Subsequent analysis using cost models, that are grounded using cognitive load as the cost, reveals which search strategies minimize the cost of interaction for a given level of output. This paper demonstrates how economics can be applied to formally model the search process. This development establishes the theoretical foundations of Interactive Information Retrieval, providing numerous directions for empirical experimentation that are motivated directly from theory.

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“…IIR research explores the complex sequence of interactions a user may have with a search ranking within the static framework [28], largely motivated by the contradictory results found from conventional Cranfield style evaluation [7] and observational user studies [14]. With the exception of the IIR-PRP framework which we cover in more detail in Section 3.3.1, for the remainder of this paper any reference to interactive IR instead reflects the framework defined in this paper.…”

Section: Interactive Information Retrieval (Iir)mentioning

confidence: 99%

Dynamic Information Retrieval

Sloan

Wang

2015

Proceedings of the 2015 International Conference on the Theory of Information Retrieval

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Theoretical frameworks like the Probability Ranking Principle and its more recent Interactive Information Retrieval variant have guided the development of ranking and retrieval algorithms for decades, yet they are not capable of helping us model problems in Dynamic Information Retrieval which exhibit the following three properties; an observable user signal, retrieval over multiple stages and an overall search intent. In this paper a new theoretical framework for retrieval in these scenarios is proposed. We derive a general dynamic utility function for optimizing over these types of tasks, that takes into account the utility of each stage and the probability of observing user feedback. We apply our framework to experiments over TREC data in the dynamic multi page search scenario as a practical demonstration of its effectiveness and to frame the discussion of its use, its limitations and to compare it against the existing frameworks.

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Interactive information retrieval

Cited by 83 publications

References 194 publications

How query cost affects search behavior

How query cost affects search behavior

The economics in interactive information retrieval

Dynamic Information Retrieval

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