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A Computational Cognitive Model of Information Search in Textual Materials

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Abstract

Document foraging for information is a crucial and increasingly prevalent activity nowadays. We designed a computational cognitive model to simulate the oculomotor scanpath of an average web user searching for specific information from textual materials. In particular, the developed model dynamically combines visual, semantic, and memory processes to predict the user’s focus of attention during information seeking from paragraphs of text. A series of psychological experiments was conducted using eye-tracking techniques in order to validate and refine the proposed model. Comparisons between model simulations and human data are reported and discussed taking into account the strengths and shortcomings of the model. The proposed model provides a unique contribution to the investigation of the cognitive processes involved during information search and bears significant implications for web page design and evaluation.

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Notes

  1. The algorithm used is available at the following web site: www.svi.cps.utexas.edu.

  2. The Levenhstein distance between two strings is the minimal number of basic operations (addition, deletion or replacement of a character) to transform one string into the other. For instance, 4 operations are needed to transform a U-path (coded 12348765) into an inverted-N-path (12345678).

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Acknowledgments

We thank Maria Ktori and Erik Reichle for their insightful feedback on a previous version of the manuscript. This research was supported by the ANR (French Research National Agency) project Eye-LSA.

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Authors and Affiliations

  1. Laboratoire de Psychologie Cognitive UMR 7290, CNRS & Aix-Marseille Université, Case D, Bât 9, 3 Place Victor Hugo, 13331, Marseille Cedex 3, France

    Myriam Chanceaux

  2. GIPSA-Lab, University of Grenoble, Grenoble, France

    Anne Guérin-Dugué

  3. LPNC, University of Grenoble, Grenoble, France

    Benoît Lemaire

  4. LUTIN, University of Paris VIII, Paris, France

    Thierry Baccino

Authors
  1. Myriam Chanceaux
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  2. Anne Guérin-Dugué
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  3. Benoît Lemaire
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  4. Thierry Baccino
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Correspondence to Myriam Chanceaux.

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Chanceaux, M., Guérin-Dugué, A., Lemaire, B. et al. A Computational Cognitive Model of Information Search in Textual Materials. Cogn Comput 6, 1–17 (2014). https://doi.org/10.1007/s12559-012-9200-1

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  • DOI: https://doi.org/10.1007/s12559-012-9200-1

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