SNIF-ACT: A Model of Information Foraging on the World Wide Web

  • Peter Pirolli
  • Wai-Tat Fu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2702)


SNIF-ACT (Scent-based Navigation and Information Foraging in the ACT architecture) has been developed to simulate users as they perform unfamiliar information-seeking tasks on the World Wide Web (WWW). SNIF-ACT selects actions based on the measure of information scent, which is calculated by a spreading activation mechanism that captures the mutual relevance of the contents of a WWW page to the goal of the user. There are two main predictions of SNIF-ACT: (1) users working on unfamiliar tasks are expected to choose links that have high information scent, (2) users will leave a site when the information scent of the site diminishes below a certain threshold. SNIF-ACT produced good fits to data collected from four users working on two tasks each. The results suggest that the current content-based spreading activation SNIF-ACT model is able to generate useful predictions about complex user-WWW interactions.


Production Rule Spreading Activation Mutual Relevance Unfamiliar Task Information Forage 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Peter Pirolli
    • 1
  • Wai-Tat Fu
    • 1
  1. 1.PARCPalo Alto

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