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IGroup: a web image search engine with semantic clustering of search results

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Wei-Ying MaAuthors Info & Claims

MM '06: Proceedings of the 14th ACM international conference on Multimedia

Pages 497 - 498

https://doi.org/10.1145/1180639.1180743

Published: 23 October 2006 Publication History

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Abstract

In this demo, we present IGroup, a Web image search engine that organizes the search results into semantic clusters. Different from all existing Web image search results clustering algorithms that only cluster the top few images using visual or textual features, IGroup first identifies several query-related semantic clusters based on a key phrases extraction algorithm originally proposed for clustering general Web search results. Then, all the resulting images are separated and assigned to corresponding clusters. To make the best use of the clustering results, a new user interface is proposed. Please go to http://igroup.msra.cn for real experience.

References

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Google, http://www.google.com.

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Google Image, http://images.google.com

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[3]

H. J. Zeng, Q. C. He, Z. Chen, W. Y. Ma and J. W. Ma, "Learning to cluster Web search results", Proceedings of the 27th annual international ACM SIGIR conference, pp: 210 -- 217.

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[4]

Picsearch image search, http://www.picsearch.com

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Yahoo image search, http://images.search.yahoo.com/

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Cited By

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Zhao KCai ZSui QWei EZhu K(2022)Clustering Image Search Results by Entity DisambiguationMachine Learning and Knowledge Discovery in Databases10.1007/978-3-662-44845-8_24(369-384)Online publication date: 10-Mar-2022
https://dl.acm.org/doi/10.1007/978-3-662-44845-8_24
Patil S(2021)Content Based Image and Video Retrieval A Compressive ReviewInternational Journal of Engineering and Advanced Technology10.35940/ijeat.E2783.061052110:5(243-247)Online publication date: 30-Jun-2021
https://doi.org/10.35940/ijeat.E2783.0610521
Petridis SShin HChilton L(2021)SymbolFinder: Brainstorming Diverse Symbols Using Local Semantic NetworksThe 34th Annual ACM Symposium on User Interface Software and Technology10.1145/3472749.3474757(385-399)Online publication date: 10-Oct-2021
https://dl.acm.org/doi/10.1145/3472749.3474757
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IGroup: a web image search engine with semantic clustering of search results

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IGroup: web image search results clustering
MM '06: Proceedings of the 14th ACM international conference on Multimedia

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Published In

MM '06: Proceedings of the 14th ACM international conference on Multimedia

October 2006

1072 pages

ISBN:1595934472

DOI:10.1145/1180639

General Chairs:
Klara Nahrstedt
UIUC
,
Matthew Turk
UCSB
,
Program Chairs:
Yong Rui
Microsoft Research
,
Wolfgang Klas
Universität Wien
,
Ketan Mayer-Patel
UNC

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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Association for Computing Machinery

New York, NY, United States

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Published: 23 October 2006

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MM06: The 14th ACM International Conference on Multimedia 2006

October 23 - 27, 2006

CA, Santa Barbara, USA

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Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Zhao KCai ZSui QWei EZhu K(2022)Clustering Image Search Results by Entity DisambiguationMachine Learning and Knowledge Discovery in Databases10.1007/978-3-662-44845-8_24(369-384)Online publication date: 10-Mar-2022
https://dl.acm.org/doi/10.1007/978-3-662-44845-8_24
Patil S(2021)Content Based Image and Video Retrieval A Compressive ReviewInternational Journal of Engineering and Advanced Technology10.35940/ijeat.E2783.061052110:5(243-247)Online publication date: 30-Jun-2021
https://doi.org/10.35940/ijeat.E2783.0610521
Petridis SShin HChilton L(2021)SymbolFinder: Brainstorming Diverse Symbols Using Local Semantic NetworksThe 34th Annual ACM Symposium on User Interface Software and Technology10.1145/3472749.3474757(385-399)Online publication date: 10-Oct-2021
https://dl.acm.org/doi/10.1145/3472749.3474757
Singh SKumar P(2018)User specific context construction for personalized multimedia retrievalMultimedia Tools and Applications10.1007/s11042-017-4961-x77:11(13459-13486)Online publication date: 1-Jun-2018
https://dl.acm.org/doi/10.1007/s11042-017-4961-x
Dange BKshirsagar D(2017)Hashing based re-ranking of web images using query-specific semantic signatures2017 1st International Conference on Intelligent Systems and Information Management (ICISIM)10.1109/ICISIM.2017.8122168(164-170)Online publication date: Oct-2017
https://doi.org/10.1109/ICISIM.2017.8122168
Yan YLiu GWang SZhang JZheng K(2017)Graph-based clustering and ranking for diversified image searchMultimedia Systems10.1007/s00530-014-0419-423:1(41-52)Online publication date: 1-Feb-2017
https://dl.acm.org/doi/10.1007/s00530-014-0419-4
Sejal DGaneshsingh TVenugopal KIyengar SPatnaik L(2016)Image Recommendation Based on ANOVA Cosine SimilarityProcedia Computer Science10.1016/j.procs.2016.06.09189(562-567)Online publication date: 2016
https://doi.org/10.1016/j.procs.2016.06.091
Tang YZhang HXu B(2015)Metadata Organization and Retrieval with Attribute Tree for Large-Scale Traffic Surveillance VideosBig Data Computing and Communications10.1007/978-3-319-22047-5_35(434-443)Online publication date: 24-Jul-2015
https://doi.org/10.1007/978-3-319-22047-5_35
Wang JJiang YWang QYang KNgo CHua KRui YSteinmetz RHanjalic ANatsev AZhu W(2014)Organizing Video Search Results to Adapted Semantic Hierarchies for Topic-based BrowsingProceedings of the 22nd ACM international conference on Multimedia10.1145/2647868.2655012(845-848)Online publication date: 3-Nov-2014
https://dl.acm.org/doi/10.1145/2647868.2655012
Mei TRui YLi STian Q(2014)Multimedia search rerankingACM Computing Surveys10.1145/253679846:3(1-38)Online publication date: 1-Jan-2014
https://dl.acm.org/doi/10.1145/2536798
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Mining query subtopics from search log data

IGroup: presenting web image search results in semantic clusters

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