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Query expansion using gaze-based feedback on the subdocument level

Published: 20 July 2008 Publication History

Abstract

We examine the effect of incorporating gaze-based attention feedback from the user on personalizing the search process. Employing eye tracking data, we keep track of document parts the user read in some way. We use this information on the subdocument level as implicit feedback for query expansion and reranking.
We evaluated three different variants incorporating gaze data on the subdocument level and compared them against a baseline based on context on the document level. Our results show that considering reading behavior as feedback yields powerful improvements of the search result accuracy of ca. 32% in the general case. However, the extent of the improvements varies depending on the internal structure of the viewed documents and the type of the current information need.

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    cover image ACM Conferences
    SIGIR '08: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
    July 2008
    934 pages
    ISBN:9781605581644
    DOI:10.1145/1390334
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 20 July 2008

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    Author Tags

    1. eye tracking
    2. implicit feedback
    3. personalization
    4. reading

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    • (2024)Eye-Tracking Study into Patterns of Attention to Environmental Media Texts among Youth Audiences in the Context of the Communicative Strategy2024 Communication Strategies in Digital Society Seminar (ComSDS)10.1109/ComSDS61892.2024.10502069(83-88)Online publication date: 10-Apr-2024
    • (2022)Cognitive differences between readers attentive and inattentive to task-related information: an eye-tracking studyAslib Journal of Information Management10.1108/AJIM-01-2022-000775:5(917-939)Online publication date: 4-Oct-2022
    • (2021)Does More Context Help? Effects of Context Window and Application Source on Retrieval PerformanceACM Transactions on Information Systems10.1145/347405540:2(1-40)Online publication date: 27-Sep-2021
    • (2020)Factuality Checking in News Headlines with Eye TrackingProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401221(2013-2016)Online publication date: 25-Jul-2020
    • (2020)Detecting Relevance during Decision-Making from Eye Movements for UI AdaptationACM Symposium on Eye Tracking Research and Applications10.1145/3379155.3391321(1-11)Online publication date: 2-Jun-2020
    • (2020)The Role of Word-Eye-Fixations for Query Term PredictionProceedings of the 2020 Conference on Human Information Interaction and Retrieval10.1145/3343413.3378010(422-426)Online publication date: 14-Mar-2020
    • (2019)Reading ProtocolProceedings of the 2019 Conference on Human Information Interaction and Retrieval10.1145/3295750.3298921(73-81)Online publication date: 8-Mar-2019
    • (2019)Explicating "Implicit Interaction"Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems10.1145/3290605.3300647(1-16)Online publication date: 2-May-2019
    • (2018)An Effective of Data Organizing Method Combines with Naïve Bayes for Vietnamese Document RetrievalContext-Aware Systems and Applications, and Nature of Computation and Communication10.1007/978-3-319-77818-1_20(205-213)Online publication date: 16-Mar-2018
    • (2017)Automatic Classification of Users’ Health Information Need Context: Logistic Regression Analysis of Mouse-Click and Eye-Tracker DataJournal of Medical Internet Research10.2196/jmir.835419:12(e424)Online publication date: 21-Dec-2017
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