Platform for Evaluation of Readers' Implicit Feedback Using Eye-Tracking

Miroslav Živković, Egon L. van den Broek, Frans van der Sluis

    Abstract

    Large amounts of information are nowadays easily obtainable using the Internet, and using implicit feedback whether a reader finds a text interesting is desirable. Eye-tracking technology could be used for such a feedback, and a combination of eye-movement features and a textual complexity measure can be used to predict the user's interest. In this paper we give an overview of a platform developed to evaluate and visualize implicit feedback of a person who reads a text. Based on the eye-movement samples provided, a model is trained that could be used to predict comprehensibility of a user reading a text. This prediction is combined with objective complexity evaluation of the text using data mining methods, and the outcome is used to select a text (from a repository) that a user may find more valuable (interesting). We briefly discuss the requirements, architecture and implementation of this platform.
    Original languageEnglish
    Title of host publicationECCE'18: Proceedings of the 36th European Conference on Cognitive Ergonomics
    Number of pages4
    Volume36
    Place of PublicationNew York, NY, USA
    PublisherAssociation for Computing Machinery
    Publication date5 Sept 2018
    Article number13
    ISBN (Print)978-1-4503-6449-2
    DOIs
    Publication statusPublished - 5 Sept 2018
    EventEuropean Conference on Cognitive Ergonomics - Utrecht, Netherlands
    Duration: 5 Sept 20187 Sept 2018
    Conference number: 36

    Conference

    ConferenceEuropean Conference on Cognitive Ergonomics
    Number36
    Country/TerritoryNetherlands
    CityUtrecht
    Period05/09/201807/09/2018
    SeriesECCE'18

    Fingerprint

    Dive into the research topics of 'Platform for Evaluation of Readers' Implicit Feedback Using Eye-Tracking'. Together they form a unique fingerprint.

    Cite this