46 research outputs found

    Exploring opportunities to facilitate serendipity in search

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    Serendipitously discovering new information can bring many benefits. Although we can design systems to highlight serendipitous information, serendipity cannot be easily orchestrated and is thus hard to study. In this paper, we deployed a working search engine that matched search results with Facebook `Like' data, as a technology probe to examine naturally occurring serendipitous discoveries. Search logs and diary entries revealed the nature of these occasions in both leisure and work contexts. The findings support the use of the micro-serendipity model in search system design

    Modelling interaction with economic models of search

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    Understanding how people interact when searching is central to the study of Interactive Information Retrieval (IIR). Most of the prior work has either been conceptual, observational or empirical. While this has led to numerous insights and findings regarding the interaction between users and systems, the theory has lagged behind. In this paper, we extend the recently proposed search economic theory to make the model more realistic. We then derive eight interaction based hypotheses regarding search behaviour. To validate the model, we explore whether the search behaviour of thirty-six participants from a lab based study is consistent with the theory. Our analysis shows that observed search behaviours are in line with predicted search behaviours and that it is possible to provide credible explanations for such behaviours. This work describes a concise and compact representation of search behaviour providing a strong theoretical basis for future IIR research
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