extended-abstract

A classification scheme for user intentions in image search

Authors:

Mathias Lux,

Christoph Kofler,

Oge MarquesAuthors Info & Claims

CHI EA '10: CHI '10 Extended Abstracts on Human Factors in Computing Systems

Pages 3913 - 3918

https://doi.org/10.1145/1753846.1754078

Published: 10 April 2010 Publication History

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Abstract

Searching for images on the web is still an open problem. While multiple approaches have been presented, there has been surprisingly little work on the actual goals and intentions of users. In this poster we present our classification scheme for user goals in image search and describe our ongoing work focusing on identification and classification of user intentions during image search tasks.

References

[1]

A. Broder. A Taxonomy of Web Search, SIGIR Forum, 36(2):3--10, 2002.

Digital Library

Google Scholar

[2]

B. J. Jansen, D. L. Booth, and A. Spink. Determining the informational, navigational, and transactional intent of Web queries. Inf. Process. Manage., 44(3):1251-1266-2008.

Digital Library

Google Scholar

[3]

D. E. Rose and D. Levinson. Understanding user goals in web search. In WWW '04: Proceedings of the 13th international conference on World Wide Web, pages 13--19, New York, NY, USA, 2004. ACM.

Digital Library

Google Scholar

[4]

C. Kofler and M. Lux. An Exploratory Study on the Explicitness of User Intentions in Digital Photo Retrieval. In I-KNOW '09: Proceedings of the 9th International Conference on Knowledge Management and Knowledge Technologies, 2009.

Google Scholar

[5]

M. Strohmaier, M. Lux, M. Granitzer, P. Scheir, S. Liaskos, and E. Yu. How Do Users Express Goals on the Web? - An Exploration of Intentional Structures in Web Search. In We Know'07 International Workshop on Collaborative Knowledge Management for Web Information Systems, in conjunction with WISE'07, Nancy, France, 2007.

Digital Library

Google Scholar

[6]

C. Kofler and M. Lux. Dynamic Presentation Adaptation based on User Intent Classification. In MM '09: Proceedings of the seventeen ACM international conference on Multimedia, pages 1117--1118, New York, NY, USA, 2009. ACM.

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Cited By

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Ukkonen AJoona PRuotsalo THuang JChang YCheng XKamps JMurdock VWen JLiu Y(2020)Generating Images Instead of Retrieving ThemProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401129(1329-1338)Online publication date: 25-Jul-2020
https://dl.acm.org/doi/10.1145/3397271.3401129
Wu ZZhou KLiu YZhang MMa S(2019)Does Diversity Affect User Satisfaction in Image SearchACM Transactions on Information Systems10.1145/332011837:3(1-30)Online publication date: 8-May-2019
https://dl.acm.org/doi/10.1145/3320118
Ding XChen Z(2019)Improving Saliency Detection Based on Modeling Photographer's IntentionIEEE Transactions on Multimedia10.1109/TMM.2018.285138921:1(124-134)Online publication date: Jan-2019
https://doi.org/10.1109/TMM.2018.2851389
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Index Terms

A classification scheme for user intentions in image search
1. Human-centered computing
  1. Human computer interaction (HCI)

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Information

Published In

CHI EA '10: CHI '10 Extended Abstracts on Human Factors in Computing Systems

April 2010

2219 pages

ISBN:9781605589305

DOI:10.1145/1753846

General Chairs:
Elizabeth Mynatt
Georgia Institute of Technology
,
Don Schoner
Georgia Institute of Technology
,
Program Chairs:
Geraldine Fitzpatrick
Vienna University of Technology
,
Scott Hudson
Carnegie Mellon University
,
Keith Edwards
Georgia Tech
,
Tom Rodden
University of Nottingham

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 April 2010

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Extended-abstract

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CHI '10

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SIGCHI

CHI '10: CHI Conference on Human Factors in Computing Systems

April 10 - 15, 2010

Georgia, Atlanta, USA

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CHI EA '10 Paper Acceptance Rate 350 of 1,346 submissions, 26%;

Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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Ukkonen AJoona PRuotsalo THuang JChang YCheng XKamps JMurdock VWen JLiu Y(2020)Generating Images Instead of Retrieving ThemProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401129(1329-1338)Online publication date: 25-Jul-2020
https://dl.acm.org/doi/10.1145/3397271.3401129
Wu ZZhou KLiu YZhang MMa S(2019)Does Diversity Affect User Satisfaction in Image SearchACM Transactions on Information Systems10.1145/332011837:3(1-30)Online publication date: 8-May-2019
https://dl.acm.org/doi/10.1145/3320118
Ding XChen Z(2019)Improving Saliency Detection Based on Modeling Photographer's IntentionIEEE Transactions on Multimedia10.1109/TMM.2018.285138921:1(124-134)Online publication date: Jan-2019
https://doi.org/10.1109/TMM.2018.2851389
Xie XLiu Yde Rijke MHe JZhang MMa SChang YZhai CLiu YMaarek Y(2018)Why People Search for Images using Web Search EnginesProceedings of the Eleventh ACM International Conference on Web Search and Data Mining10.1145/3159652.3159686(655-663)Online publication date: 2-Feb-2018
https://dl.acm.org/doi/10.1145/3159652.3159686
Soleymani MRiegler MHalvorsen P(2018)Multimodal analysis of user behavior and browsed content under different image search intentsInternational Journal of Multimedia Information Retrieval10.1007/s13735-018-0150-67:1(29-41)Online publication date: 29-Jan-2018
https://doi.org/10.1007/s13735-018-0150-6
Wang BLarson MAlameda-Pineda XRedi MSoleymani MSebe NChang SGosling S(2017)Beyond Concept DetectionProceedings of the Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes10.1145/3132515.3132521(11-19)Online publication date: 27-Oct-2017
https://dl.acm.org/doi/10.1145/3132515.3132521
Soleymani MRiegler MHalvorsen PIonescu BSebe NFeng JLarson MLienhart RSnoek C(2017)Multimodal Analysis of Image Search IntentProceedings of the 2017 ACM on International Conference on Multimedia Retrieval10.1145/3078971.3078995(251-259)Online publication date: 6-Jun-2017
https://dl.acm.org/doi/10.1145/3078971.3078995
Anohah ESuhonen J(2016)MEASURING EFFECT OF CULTURALLY RESPONSIVE LEARNING ENVIRONMENT FOR COMPUTING EDUCATION IN AFRICAN CONTEXTProblems of Education in the 21st Century10.33225/pec/16.73.0673:1(6-17)Online publication date: 25-Oct-2016
https://doi.org/10.33225/pec/16.73.06
Kofler CLarson MHanjalic A(2016)User Intent in Multimedia SearchACM Computing Surveys10.1145/295493049:2(1-37)Online publication date: 13-Aug-2016
https://dl.acm.org/doi/10.1145/2954930
Riegler MCalvet LCalvet AHalvorsen PGriwodz CFeng WZink M(2015)Exploitation of producer intent in relation to bandwidth and QoE for online video streaming servicesProceedings of the 25th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video10.1145/2736084.2736095(7-12)Online publication date: 18-Mar-2015
https://dl.acm.org/doi/10.1145/2736084.2736095
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Why do young people tag photos on social networking sites? Explaining user intentions

User perception, intention, and attitude on mobile advertising

Ubiquitous Computing Acceptance Model: end user concern about security, privacy and risk

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