SNIF-ACT: A model of information foraging on the World Wide Web

Peter Pirolli, Wai Tat Fu

Research output: Contribution to journalConference articlepeer-review


SNIP-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). SNIP-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 SNIP-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. SNIP-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 SNIP-ACT model is able to generate useful predictions about complex user-WWW interactions.

Original languageEnglish (US)
Pages (from-to)45-54
Number of pages10
JournalLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
StatePublished - 2003
Externally publishedYes
Event9th International Conference, UM 2003 - Johnstown, PA, United States
Duration: Jun 22 2003Jun 26 2003

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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