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Web image retrieval reranking with multi-view clustering

Authors:

Xiangyang XueAuthors Info & Claims

WWW '09: Proceedings of the 18th international conference on World wide web

Pages 1189 - 1190

https://doi.org/10.1145/1526709.1526922

Published: 20 April 2009 Publication History

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Abstract

General image retrieval is often carried out by a text-based search engine, such as Google Image Search. In this case, natural language queries are used as input to the search engine. Usually, the user queries are quite ambiguous and the returned results are not well-organized as the ranking often done by the popularity of an image. In order to address these problems, we propose to use both textual and visual contents of retrieved images to reRank web retrieved results. In particular, a machine learning technique, a multi-view clustering algorithm is proposed to reorganize the original results provided by the text-based search engine. Preliminary results validate the effectiveness of the proposed framework.

References

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R. Baeza--Yates and B. Ribeiro-Neto. Modern Information Retrieval. Addison Wesley, 1999.

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[2]

S. Bickel and T. Scheffer. Multi-view clustering. In ICDM '04: Proceedings of the Fourth IEEE International Conference on Data Mining, pages 19--26, 2004.

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X. S. Zhou and T. S. Huang. Relevance feedback in image retrieval: A comprehensive review. Multimedia Systems, 8(6):536--544, 2003.

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Cited By

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Kozłowski MBuczkowski PBrzezinski P(2023)A Novel Process of Shoe Pairing Using Computer Vision and Deep Learning MethodsDigital Interaction and Machine Intelligence10.1007/978-3-031-37649-8_4(35-44)Online publication date: 25-Jul-2023
https://doi.org/10.1007/978-3-031-37649-8_4
Huang AChen WZhao TChen C(2021)Joint Learning of Latent Similarity and Local Embedding for Multi-View ClusteringIEEE Transactions on Image Processing10.1109/TIP.2021.309608630(6772-6784)Online publication date: 2021
https://doi.org/10.1109/TIP.2021.3096086
Chao GSun SBi J(2021)A Survey on Multiview ClusteringIEEE Transactions on Artificial Intelligence10.1109/TAI.2021.30658942:2(146-168)Online publication date: Apr-2021
https://doi.org/10.1109/TAI.2021.3065894
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Index Terms

Web image retrieval reranking with multi-view clustering
1. Information systems
  1. Information retrieval

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Information & Contributors

Information

Published In

WWW '09: Proceedings of the 18th international conference on World wide web

April 2009

1280 pages

ISBN:9781605584874

DOI:10.1145/1526709

General Chairs:
Juan Quemada
DIT-UPM
,
Gonzalo León
DIT-UPM
,
Program Chairs:
Yoelle Maarek
Google Inc., Israel
,
Wolfgang Nejdl
L3S and Hannover University

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 April 2009

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WWW '09

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WWW '09: The 18th International World Wide Web Conference

April 20 - 24, 2009

Madrid, Spain

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

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Kozłowski MBuczkowski PBrzezinski P(2023)A Novel Process of Shoe Pairing Using Computer Vision and Deep Learning MethodsDigital Interaction and Machine Intelligence10.1007/978-3-031-37649-8_4(35-44)Online publication date: 25-Jul-2023
https://doi.org/10.1007/978-3-031-37649-8_4
Huang AChen WZhao TChen C(2021)Joint Learning of Latent Similarity and Local Embedding for Multi-View ClusteringIEEE Transactions on Image Processing10.1109/TIP.2021.309608630(6772-6784)Online publication date: 2021
https://doi.org/10.1109/TIP.2021.3096086
Chao GSun SBi J(2021)A Survey on Multiview ClusteringIEEE Transactions on Artificial Intelligence10.1109/TAI.2021.30658942:2(146-168)Online publication date: Apr-2021
https://doi.org/10.1109/TAI.2021.3065894
Mai HKim M(2014)Utilizing similarity relationships among existing data for high accuracy processing of content-based image retrievalMultimedia Tools and Applications10.1007/s11042-013-1360-972:1(331-360)Online publication date: 1-Sep-2014
https://dl.acm.org/doi/10.1007/s11042-013-1360-9
Lu HJiang GYang BXue X(2013)An Adaptive Query Prototype Modeling Method for Image Search RerankingProceedings of the 2013 IEEE International Conference on Computer Vision Workshops10.1109/ICCVW.2013.52(339-346)Online publication date: 2-Dec-2013
https://dl.acm.org/doi/10.1109/ICCVW.2013.52
Saha M(2013)A Graph Based Approach to Multiview ClusteringPattern Recognition and Machine Intelligence10.1007/978-3-642-45062-4_17(128-133)Online publication date: 2013
https://doi.org/10.1007/978-3-642-45062-4_17
Eaton EdesJardins MJacob S(2012)Multi-view constrained clustering with an incomplete mapping between viewsKnowledge and Information Systems10.1007/s10115-012-0577-738:1(231-257)Online publication date: 21-Nov-2012
https://doi.org/10.1007/s10115-012-0577-7
Li PMa JGao S(2011)Actions in stillweb imagesProceedings of the 12th international conference on Web-age information management10.5555/2035562.2035598(302-313)Online publication date: 14-Sep-2011
https://dl.acm.org/doi/10.5555/2035562.2035598
Li PMa JGao S(2011)Actions in Still Web Images: Visualization, Detection and RetrievalWeb-Age Information Management10.1007/978-3-642-23535-1_27(302-313)Online publication date: 2011
https://doi.org/10.1007/978-3-642-23535-1_27
Li PZhang LMa JLi SGao XSebe N(2010)Dual-ranking for web image retrievalProceedings of the ACM International Conference on Image and Video Retrieval10.1145/1816041.1816068(166-173)Online publication date: 5-Jul-2010
https://dl.acm.org/doi/10.1145/1816041.1816068

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