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This paper models user navigation within information architectures as a sequential decision-making process under memory constraints, extending the concept of information scent. The model incorporates both local and global information scent, but limits the amount of information users can process on each page due to time budgets and memory limitations. By simulating strategic inspection and premature selections, the model replicates key navigation behaviors like wrong turns and backtracking, validated against empirical data.
Trial-and-error navigation, often seen as irrational, can be explained as an optimal strategy under memory constraints and time pressure when users strategically sample information scent.
Users often struggle to locate an item within an information architecture, particularly when links are ambiguous or deeply nested in hierarchies. Information scent has been used to explain why users select incorrect links, but this concept assumes that users see all available links before deciding. In practice, users frequently select a link too quickly, overlook relevant cues, and then rely on backtracking when errors occur. We extend the concept of information scent by framing navigation as a sequential decision-making problem under memory constraints. Specifically, we assume that users do not scan entire pages but instead inspect strategically, looking"just enough"to find the target given their time budget. To choose which item to inspect next, they consider both local (this page) and global (site) scent; however, both are constrained by memory. Trying to avoid wasting time, they occasionally choose the wrong links without inspecting everything on a page. Comparisons with empirical data show that our model replicates key navigation behaviors: premature selections, wrong turns, and recovery from backtracking. We conclude that trial-and-error behavior is well explained by information scent when accounting for the sequential and bounded characteristics of the navigation problem.