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An Analysis of Theories of Search and Search Behavior
Author(s) -
Leif Azzopardi,
Guido Zuccon
Publication year - 2015
Publication title -
qut eprints (queensland university of technology)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/2808194.2809447
Subject(s) - computer science , ranking (information retrieval) , perspective (graphical) , order (exchange) , artificial intelligence , information retrieval , machine learning , theoretical computer science , economics , finance
Theories of search and search behavior can be used to glean insights and generate hypotheses about how people interact with retrieval systems. This paper examines three such theories, the long standing Information Foraging Theory, along with the more recently proposed Search Economic Theory and the Interactive Probability Ranking Principle. Our goal is to develop a model for ad-hoc topic retrieval using each approach, all within a common framework, in order to (1) determine what predictions each approach makes about search behavior, and (2) show the relationships, equivalences and differences between the approaches. While each approach takes a different perspective on modeling searcher interactions, we show that under certain assumptions, they lead to similar hypotheses regarding search behavior. Moreover, we show that the models are complementary to each other, but operate at different levels (i.e., sessions, patches and situations). We further show how the differences between the approaches lead to new insights into the theories and new models. This contribution will not only lead to further theoretical developments, but also enables practitioners to employ one of the three equivalent models depending on the data available

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