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Image Sense Classification in Text-Based Image Retrieval

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Information Retrieval Technology (AIRS 2009)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5839))

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Abstract

An image sense is a graphic representation of a concept denoted by a (set of) term(s). This paper proposes algorithms to find image senses for a concept, collect the sense descriptions, and employ them to disambiguate the image senses in text-based image retrieval. In the experiments on 10 ambiguous terms, 97.12% of image senses returned by a search engine are covered. The average precision of sample images is 68.26%. We propose four kinds of classifiers using text, image, URL, and expanded text features, respectively, and a merge strategy to combine the results of these classifiers. The merge classifier achieves 0.3974 in F-measure (β=0.5), which is much better than the baseline and has 51.61% of human performance.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan

    Yih-Chen Chang & Hsin-Hsi Chen

Authors
  1. Yih-Chen Chang
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  2. Hsin-Hsi Chen
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Pohang University of Science and Technology, San 31, Hyoja-dong, Nam-gu, 790-784, Pohang, Korea

    Gary Geunbae Lee

  2. School of Computing, The Robert Gordon University, St Andrew Street, AB25 1HG, Aberdeen, UK

    Dawei Song

  3. Microsoft Reseach Asia, 5F Beijing Sigma Center, 49 Zhichun Road, Haidian District, 100190, Beijing, P.R. China

    Chin-Yew Lin

  4. National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, 101-8430, Tokyo, Japan

    Akiko Aizawa

  5. School of Literature, Shirayuri College, 1-25 Midorigaoka, Chofu-shi, 182-8525, Tokyo, Japan

    Kazuko Kuriyama

  6. Graduate School of Information Science and Technology, Hokkaido University, North 14 West 9, Kita-ku. Sapporo-shi, 060-0814, Hokkaido, Japan

    Masaharu Yoshioka

  7. Microsoft Research Asia, 5F Beijing Sigma Center, 49 Zhichun Road, Haidian District, 100190, Beijing, P.R. China

    Tetsuya Sakai

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© 2009 Springer-Verlag Berlin Heidelberg

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Chang, YC., Chen, HH. (2009). Image Sense Classification in Text-Based Image Retrieval. In: Lee, G.G., et al. Information Retrieval Technology. AIRS 2009. Lecture Notes in Computer Science, vol 5839. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04769-5_11

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  • DOI: https://doi.org/10.1007/978-3-642-04769-5_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04768-8

  • Online ISBN: 978-3-642-04769-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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