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    Linking search tasks with low-level eye movement patterns


    Cole, Michael J. and Gwizdka, Jacek and Bierig, Ralf and Belkin, Nicholas J. and Liu, Jingjing and Liu, Chang and Zhang, Xiangmin (2010) Linking search tasks with low-level eye movement patterns. Proceedings of the 28th annual conference of the European Association of Cognitive Ergonomics. pp. 109-116.

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    Abstract

    Motivation -- On-the-task detection of the task type and task attributes can benefit personalization and adaptation of information systems. Research approach -- A web-based information search experiment was conducted with 32 participants using a multi-stream logging system. The realistic tasks were related directly to the backgrounds of the participants and were of distinct task types. Findings/Design -- We report on a relationship between task and individual reading behaviour. Specifically we show that transitions between scanning and reading behaviour in eye movement patterns are an implicit indicator of the current task. Research limitations/Implications -- This work suggests it is plausible to infer the type of information task from eye movement patterns. One limitation is a lack of knowledge about the general reading model differences across different types of tasks in the population. Although this is an experimental study we argue it can be generalized to real world text-oriented information search tasks. Originality/Value -- This research presents a new methodology to model user information search task behaviour. It suggests promise for detection of information task type based on patterns of eye movements. Take away message -- With increasingly complex computer interaction, knowledge about the type of information task can be valuable for system personalization. Modelling the reading/scanning patterns of eye movements can allow inference about the task type and task attributes.

    Item Type: Article
    Keywords: Personalization; cognitive task; interactive information retrieval; information search; user models; eye movements; user study;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 15222
    Identification Number: https://doi.org/10.1145/1962300.1962323
    Depositing User: Ralf Bierig
    Date Deposited: 11 Jan 2022 15:42
    Journal or Publication Title: Proceedings of the 28th annual conference of the European Association of Cognitive Ergonomics
    Publisher: ACM
    Refereed: Yes
    URI:

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