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Visual-semantic graphs: using queries to reduce the semantic gap in web image retrieval

Published: 26 October 2010 Publication History

Abstract

We explore the application of a graph representation to model similarity relationships that exist among images found on the Web. The resulting similarity-induced graph allows us to model in a unified way different types of content-based similarities, as well as semantic relationships. Content-based similarities include different image descriptors, and semantic similarities can include relevance user feedback from search engines. The goal of our representation is to provide an experimental framework for combining apparently unrelated metrics into a unique graph structure, which allows us to enhance the results of Web image retrieval. We evaluate our approach by re-ranking Web image search results.

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Cited By

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  • (2018)Extracting semantic knowledge from web context for multimedia IRMultimedia Tools and Applications10.1007/s11042-017-4997-y77:11(13853-13889)Online publication date: 1-Jun-2018
  • (2014)Inferring User Image-Search Goals Under the Implicit Guidance of UsersIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2013.225541824:3(394-406)Online publication date: 1-Mar-2014
  • (2013)Multimedia information retrieval on the social webProceedings of the 22nd International Conference on World Wide Web10.1145/2487788.2487941(349-354)Online publication date: 13-May-2013
  • Show More Cited By

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  1. Visual-semantic graphs: using queries to reduce the semantic gap in web image retrieval

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      cover image ACM Conferences
      CIKM '10: Proceedings of the 19th ACM international conference on Information and knowledge management
      October 2010
      2036 pages
      ISBN:9781450300995
      DOI:10.1145/1871437
      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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      Publication History

      Published: 26 October 2010

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      Author Tags

      1. content-based image features
      2. query log analysis
      3. web image re-ranking
      4. web image search

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      Cited By

      View all
      • (2018)Extracting semantic knowledge from web context for multimedia IRMultimedia Tools and Applications10.1007/s11042-017-4997-y77:11(13853-13889)Online publication date: 1-Jun-2018
      • (2014)Inferring User Image-Search Goals Under the Implicit Guidance of UsersIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2013.225541824:3(394-406)Online publication date: 1-Mar-2014
      • (2013)Multimedia information retrieval on the social webProceedings of the 22nd International Conference on World Wide Web10.1145/2487788.2487941(349-354)Online publication date: 13-May-2013
      • (2012)Tagging tagged imagesProceedings of the ACM multimedia 2012 workshop on Crowdsourcing for multimedia10.1145/2390803.2390807(3-8)Online publication date: 29-Oct-2012
      • (2012)Learning Semantic and Visual Similarity for Endomicroscopy Video RetrievalIEEE Transactions on Medical Imaging10.1109/TMI.2012.218830131:6(1276-1288)Online publication date: Jun-2012

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