poster

Using eye-tracking with dynamic areas of interest for analyzing interactive information retrieval

Authors:

SIGIR '12: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval

Pages 1165 - 1166

https://doi.org/10.1145/2348283.2348521

Published: 12 August 2012 Publication History

Get Access

Abstract

Based on a new framework for capturing dynamic areas of interest in eye-tracking, we model the user search process as a Markov-chain. The analysis indicates possible system improvements and yields parameter estimates for the Interactive Probability Ranking Principle (IPRP).

References

[1]

L. Azzopardi. The economics in interactive information retrieval. SIGIR '11, pages 15--24, New York, NY, USA, 2011. ACM.

Digital Library

Google Scholar

[2]

G. Buscher, A. Dengel, and L. van Elst. Eye movements as implicit relevance feedback. In CHI '08, pages 2991--2996, New York, NY, USA, 2008. ACM.

Digital Library

Google Scholar

[3]

N. Fuhr. A probability ranking principle for interactive information retrieval. Information Retrieval, 11(3):251--265, 2008.

Digital Library

Google Scholar

[4]

Z. Guan and E. Cutrell. An eye tracking study of the effect of target rank on web search. In CHI '07, pages 417--420, New York, NY, USA, 2007. ACM.

Digital Library

Google Scholar

[5]

T. Joachims, L. Granka, B. Pan, H. Hembrooke, F. Radlinski, and G. Gay. Evaluating the accuracy of implicit feedback from clicks and query reformulations in web search. ACM Trans. Inf. Syst., 25(2), 2007.

Digital Library

Google Scholar

Cited By

View all

Slavuljica ABektas KStrecker JMayer S(2024)NeighboAR: Efficient Object Retrieval using Proximity- and Gaze-based Object Grouping with an AR SystemProceedings of the ACM on Human-Computer Interaction10.1145/36555998:ETRA(1-19)Online publication date: 28-May-2024
https://dl.acm.org/doi/10.1145/3655599
S AV YN MJipeng TJ A(2024)Exploring Eye Gaze Patterns in Three Dimensions: An Innovative Visualization Dashboard2024 IEEE International Conference on Contemporary Computing and Communications (InC4)10.1109/InC460750.2024.10649178(1-6)Online publication date: 15-Mar-2024
https://doi.org/10.1109/InC460750.2024.10649178
Bickerdt JSonnenberg JGollnick CKasneci E(2021)Geopositioned 3D Areas of Interest for Gaze Analysis13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3409118.3475138(1-11)Online publication date: 9-Sep-2021
https://dl.acm.org/doi/10.1145/3409118.3475138
Show More Cited By

Index Terms

Using eye-tracking with dynamic areas of interest for analyzing interactive information retrieval
1. Information systems
  1. Information retrieval
    1. Information retrieval query processing

Recommendations

An eye-tracking-based approach to facilitate interactive video search
ICMR '11: Proceedings of the 1st ACM International Conference on Multimedia Retrieval

This paper investigates the role of gaze movements as implicit user feedback during interactive video retrieval tasks. In this context, we use a content-based video search engine to perform an interactive video retrieval experiment, during which, we ...
Compensation of head movements in mobile eye-tracking data using an inertial measurement unit
UbiComp '14 Adjunct: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication

Analysis of eye movements recorded with a mobile eye-tracker is difficult since the eye-tracking data are severely affected by simultaneous head and body movements. Automatic analysis methods developed for remote-, and tower-mounted eye-trackers do not ...
Region-of-Interest-Based Subtitle Placement Using Eye-Tracking Data of Multiple Viewers
TVX '16: Proceedings of the ACM International Conference on Interactive Experiences for TV and Online Video

We present a subtitle-placement method that reduces viewer's eye movement without interfering with the target region of interest (ROI) in a video scene. Subtitles help viewers understand foreign-language videos. However, subtitles tend to attract viewers'...

Comments

Information & Contributors

Information

Published In

SIGIR '12: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval

August 2012

1236 pages

ISBN:9781450314725

DOI:10.1145/2348283

General Chair:
William Hersh
Oregon Health & Science University, USA
,
Program Chairs:
Jamie Callan
Carnegie Mellon University, USA
,
Yoelle Maarek
Yahoo! Research, Israel
,
Mark Sanderson
Royal Melbourne Institute of Technology, Australia

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 August 2012

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Poster

Conference

SIGIR '12

Sponsor:

SIGIR

SIGIR '12: The 35th International ACM SIGIR conference on research and development in Information Retrieval

August 12 - 16, 2012

Oregon, Portland, USA

Acceptance Rates

Overall Acceptance Rate 792 of 3,983 submissions, 20%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

18
Total Citations
View Citations
469
Total Downloads

Downloads (Last 12 months)6
Downloads (Last 6 weeks)1

Reflects downloads up to 09 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Slavuljica ABektas KStrecker JMayer S(2024)NeighboAR: Efficient Object Retrieval using Proximity- and Gaze-based Object Grouping with an AR SystemProceedings of the ACM on Human-Computer Interaction10.1145/36555998:ETRA(1-19)Online publication date: 28-May-2024
https://dl.acm.org/doi/10.1145/3655599
S AV YN MJipeng TJ A(2024)Exploring Eye Gaze Patterns in Three Dimensions: An Innovative Visualization Dashboard2024 IEEE International Conference on Contemporary Computing and Communications (InC4)10.1109/InC460750.2024.10649178(1-6)Online publication date: 15-Mar-2024
https://doi.org/10.1109/InC460750.2024.10649178
Bickerdt JSonnenberg JGollnick CKasneci E(2021)Geopositioned 3D Areas of Interest for Gaze Analysis13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3409118.3475138(1-11)Online publication date: 9-Sep-2021
https://dl.acm.org/doi/10.1145/3409118.3475138
Zuo CDing LMeng L(2020)A Feasibility Study of Map-Based Dashboard for Spatiotemporal Knowledge Acquisition and AnalysisISPRS International Journal of Geo-Information10.3390/ijgi91106369:11(636)Online publication date: 27-Oct-2020
https://doi.org/10.3390/ijgi9110636
Schwerdt JKotzyba MNurnberger A(2019)Fact-Finding or Exploration: Identifying Latent Behavior Clusters in User’s Search Activities2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)10.1109/SMC.2019.8914225(1465-1471)Online publication date: Oct-2019
https://doi.org/10.1109/SMC.2019.8914225
Gwizdka JMoshfeghi YWilson M(2019)Introduction to the special issue on neuro‐information scienceJournal of the Association for Information Science and Technology10.1002/asi.2426370:9(911-916)Online publication date: 2-Aug-2019
https://dl.acm.org/doi/10.1002/asi.24263
Aker AFuhr N(2018)The Information Retrieval Group at the University of Duisburg-EssenDatenbank-Spektrum10.1007/s13222-018-0290-018:2(113-119)Online publication date: 3-Jul-2018
https://doi.org/10.1007/s13222-018-0290-0
Carevic ZLusky MHoek WMayr P(2018)Investigating exploratory search activities based on the stratagem level in digital librariesInternational Journal on Digital Libraries10.1007/s00799-017-0226-619:2-3(231-251)Online publication date: 1-Sep-2018
https://dl.acm.org/doi/10.1007/s00799-017-0226-6
Tran VFuhr N(2018)Personalised Session Difficulty Prediction in an Online Academic Search EngineDigital Libraries for Open Knowledge10.1007/978-3-030-00066-0_15(174-185)Online publication date: 5-Sep-2018
https://doi.org/10.1007/978-3-030-00066-0_15
Dungs SFuhr NKamps JKanoulas Ede Rijke MFang HYilmaz E(2017)Advanced Hidden Markov Models for Recognizing Search PhasesProceedings of the ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3121050.3121090(257-260)Online publication date: 1-Oct-2017
https://dl.acm.org/doi/10.1145/3121050.3121090
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

An eye-tracking-based approach to facilitate interactive video search

Compensation of head movements in mobile eye-tracking data using an inertial measurement unit

Region-of-Interest-Based Subtitle Placement Using Eye-Tracking Data of Multiple Viewers