demonstration

Multi-platform image search using tag enrichment

Authors:

Gareth J.F. JonesAuthors Info & Claims

SIGIR '12: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval

Page 1018

https://doi.org/10.1145/2348283.2348443

Published: 12 August 2012 Publication History

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Abstract

The number of images available online is growing steadily and current web search engines have indexed more than 10 billion images. Approaches to image retrieval are still often text-based and operate on image annotations and captions. Image annotations (i.e. image tags) are typically short, user-generated, and of varying quality, which increases the mismatch problem between query terms and image tags. For example, a user might enter the query "wedding dress" while all images are annotated with "bridal gown" or "wedding gown". This demonstration presents an image search system using reduction and expansion of image annotations to overcome vocabulary mismatch problems by enriching the sparse set of image tags.

Our image search application accepts a written query as input and produces a ranked list of result images and annotations (i.e. image tags) as output. The system integrates methods to reduce and expand the image tag set, thus decreasing the effect of sparse image tags. It builds on different image collections such as the Wikipedia image collection (http://www.imageclef.org/wikidata) and the Microsoft Office.com ClipArt collection (http://office.microsoft.com/), but can be applied to social collections such as Flickr as well. Our demonstration system runs on PCs, tablets, and smartphones, making use of advanced user interface capabilities on mobile devices.

References

[1]

J. Leveling and G. J. F. Jones. Classifying and filtering blind feedback terms to improve information retrieval effectiveness. In RIAO '10, pages 156--163. CID, 2010.

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[2]

J. Min, J. Leveling, D. Zhou, and G. J. F. Jones. Document expansion for image retrieval. In RIAO '10, pages 65--71, 2010.

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Index Terms

Multi-platform image search using tag enrichment
1. Information systems
  1. Information retrieval
    1. Information retrieval query processing

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Information & Contributors

Information

Published In

SIGIR '12: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval

August 2012

1236 pages

ISBN:9781450314725

DOI:10.1145/2348283

General Chair:
William Hersh
Oregon Health & Science University, USA
,
Program Chairs:
Jamie Callan
Carnegie Mellon University, USA
,
Yoelle Maarek
Yahoo! Research, Israel
,
Mark Sanderson
Royal Melbourne Institute of Technology, Australia

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 August 2012

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SIGIR '12

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SIGIR

SIGIR '12: The 35th International ACM SIGIR conference on research and development in Information Retrieval

August 12 - 16, 2012

Oregon, Portland, USA

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Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Towards data-driven estimation of image tag relevance using visually similar and dissimilar folksonomy images

A Multi-Directional Search technique for image annotation propagation

Social image tag enrichment based on textual similarity modeling