Congruency-based reranking

Itai Ben-Shalom; Noga Levy; Lior Wolf; Nachum Dershowitz; Adiel Ben-Shalom; Roni Shweka; Yaacov Choueka; Tamir Hazan; Yaniv Bar

doi:10.1109/CVPR.2014.270

Congruency-based reranking

Itai Ben-Shalom, Noga Levy, Lior Wolf, Nachum Dershowitz, Adiel Ben-Shalom, Roni Shweka, Yaacov Choueka, Tamir Hazan, Yaniv Bar

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We present a tool for re-ranking the results of a specific query by considering the (n+1) × (n+1) matrix of pairwise similarities among the elements of the set of n retrieved results and the query itself. The re-ranking thus makes use of the similarities between the various results and does not employ additional sources of information. The tool is based on graphical Bayesian models, which reinforce retrieved items strongly linked to other retrievals, and on repeated clustering to measure the stability of the obtained associations. The utility of the tool is demonstrated within the context of visual search of documents from the Cairo Genizah and for retrieval of paintings by the same artist and in the same style.

Original language	English
Title of host publication	Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Publisher	IEEE Computer Society
Pages	2107-2114
Number of pages	8
ISBN (Electronic)	9781479951178, 9781479951178
DOIs	https://doi.org/10.1109/CVPR.2014.270
State	Published - 24 Sep 2014
Externally published	Yes
Event	27th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014 - Columbus, United States Duration: 23 Jun 2014 → 28 Jun 2014

Publication series

Name	Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)	1063-6919

Conference

Conference	27th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014
Country/Territory	United States
City	Columbus
Period	23/06/14 → 28/06/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

clustering
genizah
graphical models
image retrieval
query retrieval
reranking

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition

Access to Document

10.1109/CVPR.2014.270

Cite this

Ben-Shalom, I., Levy, N., Wolf, L., Dershowitz, N., Ben-Shalom, A., Shweka, R., Choueka, Y., Hazan, T., & Bar, Y. (2014). Congruency-based reranking. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 2107-2114). Article 6909667 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). IEEE Computer Society. https://doi.org/10.1109/CVPR.2014.270

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abstract = "We present a tool for re-ranking the results of a specific query by considering the (n+1) × (n+1) matrix of pairwise similarities among the elements of the set of n retrieved results and the query itself. The re-ranking thus makes use of the similarities between the various results and does not employ additional sources of information. The tool is based on graphical Bayesian models, which reinforce retrieved items strongly linked to other retrievals, and on repeated clustering to measure the stability of the obtained associations. The utility of the tool is demonstrated within the context of visual search of documents from the Cairo Genizah and for retrieval of paintings by the same artist and in the same style.",

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author = "Itai Ben-Shalom and Noga Levy and Lior Wolf and Nachum Dershowitz and Adiel Ben-Shalom and Roni Shweka and Yaacov Choueka and Tamir Hazan and Yaniv Bar",

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doi = "10.1109/CVPR.2014.270",

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Ben-Shalom, I, Levy, N, Wolf, L, Dershowitz, N, Ben-Shalom, A, Shweka, R, Choueka, Y, Hazan, T & Bar, Y 2014, Congruency-based reranking. in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition., 6909667, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, pp. 2107-2114, 27th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014, Columbus, United States, 23/06/14. https://doi.org/10.1109/CVPR.2014.270

Congruency-based reranking. / Ben-Shalom, Itai; Levy, Noga; Wolf, Lior et al.
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society, 2014. p. 2107-2114 6909667 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Ben-Shalom, Itai

AU - Levy, Noga

AU - Wolf, Lior

AU - Dershowitz, Nachum

AU - Ben-Shalom, Adiel

AU - Shweka, Roni

AU - Choueka, Yaacov

AU - Hazan, Tamir

AU - Bar, Yaniv

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AB - We present a tool for re-ranking the results of a specific query by considering the (n+1) × (n+1) matrix of pairwise similarities among the elements of the set of n retrieved results and the query itself. The re-ranking thus makes use of the similarities between the various results and does not employ additional sources of information. The tool is based on graphical Bayesian models, which reinforce retrieved items strongly linked to other retrievals, and on repeated clustering to measure the stability of the obtained associations. The utility of the tool is demonstrated within the context of visual search of documents from the Cairo Genizah and for retrieval of paintings by the same artist and in the same style.

KW - clustering

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KW - graphical models

KW - image retrieval

KW - query retrieval

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Ben-Shalom I, Levy N, Wolf L, Dershowitz N, Ben-Shalom A, Shweka R et al. Congruency-based reranking. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society. 2014. p. 2107-2114. 6909667. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). doi: 10.1109/CVPR.2014.270

Congruency-based reranking

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this