University of Glasgow at ImageCLEFPhoto 2009: optimising similarity and diversity in image retrieval

Teerapong Leelanupab; Guido  Zuccon; Anuj Goyal; Martin Halvey; P Punitha; Joemon M. Jose

doi:10.1007/978-3-642-15751-6_14

University of Glasgow at ImageCLEFPhoto 2009: optimising similarity and diversity in image retrieval

Teerapong Leelanupab, Guido Zuccon, Anuj Goyal, Martin Halvey, P Punitha, Joemon M. Jose

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

Abstract

In this paper we describe the approaches adopted to generate the runs submitted to ImageCLEFPhoto 2009 with an aim to promote document diversity in the rankings. Four of our runs are text based approaches that employ textual statistics extracted from the captions of images, i.e. MMR [1] as a state of the art method for result diversification, two approaches that combine relevance information and clustering techniques, and an instantiation of Quantum Probability Ranking Principle. The fifth run exploits visual features of the provided images to re-rank the initial results by means of Factor Analysis.

Original language	English
Title of host publication	Multilingual Information Access Evaluation II - Multimedia Experiments
Subtitle of host publication	Proceedings of the 10th Workshop of the Cross-Language Evaluation Forum (CLEF 2009)
Publisher	Springer
Pages	133-141
Number of pages	9
ISBN (Print)	9783642157509
DOIs	https://doi.org/10.1007/978-3-642-15751-6_14
Publication status	Published - 2010

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Berlin Heidelberg
Volume	6242
ISSN (Print)	0302-9743

Keywords

image retrieval
ImageCLEF
diversity

Documents and Links

10.1007/978-3-642-15751-6_14

Cite this

Leelanupab, T., Zuccon, G., Goyal, A., Halvey, M., Punitha, P., & Jose, J. M. (2010). University of Glasgow at ImageCLEFPhoto 2009: optimising similarity and diversity in image retrieval. In Multilingual Information Access Evaluation II - Multimedia Experiments: Proceedings of the 10th Workshop of the Cross-Language Evaluation Forum (CLEF 2009) (pp. 133-141). (Lecture Notes in Computer Science; Vol. 6242). Springer. https://doi.org/10.1007/978-3-642-15751-6_14

Leelanupab, Teerapong ; Zuccon, Guido ; Goyal, Anuj et al. / University of Glasgow at ImageCLEFPhoto 2009: optimising similarity and diversity in image retrieval. Multilingual Information Access Evaluation II - Multimedia Experiments: Proceedings of the 10th Workshop of the Cross-Language Evaluation Forum (CLEF 2009). Springer, 2010. pp. 133-141 (Lecture Notes in Computer Science).

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title = "University of Glasgow at ImageCLEFPhoto 2009: optimising similarity and diversity in image retrieval",

abstract = "In this paper we describe the approaches adopted to generate the runs submitted to ImageCLEFPhoto 2009 with an aim to promote document diversity in the rankings. Four of our runs are text based approaches that employ textual statistics extracted from the captions of images, i.e. MMR [1] as a state of the art method for result diversification, two approaches that combine relevance information and clustering techniques, and an instantiation of Quantum Probability Ranking Principle. The fifth run exploits visual features of the provided images to re-rank the initial results by means of Factor Analysis. ",

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author = "Teerapong Leelanupab and Guido Zuccon and Anuj Goyal and Martin Halvey and P Punitha and Jose, {Joemon M.}",

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Leelanupab, T, Zuccon, G, Goyal, A, Halvey, M, Punitha, P & Jose, JM 2010, University of Glasgow at ImageCLEFPhoto 2009: optimising similarity and diversity in image retrieval. in Multilingual Information Access Evaluation II - Multimedia Experiments: Proceedings of the 10th Workshop of the Cross-Language Evaluation Forum (CLEF 2009). Lecture Notes in Computer Science, vol. 6242, Springer, pp. 133-141. https://doi.org/10.1007/978-3-642-15751-6_14

University of Glasgow at ImageCLEFPhoto 2009: optimising similarity and diversity in image retrieval. / Leelanupab, Teerapong; Zuccon, Guido ; Goyal, Anuj et al.

Multilingual Information Access Evaluation II - Multimedia Experiments: Proceedings of the 10th Workshop of the Cross-Language Evaluation Forum (CLEF 2009). Springer, 2010. p. 133-141 (Lecture Notes in Computer Science; Vol. 6242).

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

TY - GEN

T1 - University of Glasgow at ImageCLEFPhoto 2009: optimising similarity and diversity in image retrieval

AU - Leelanupab, Teerapong

AU - Zuccon, Guido

AU - Goyal, Anuj

AU - Halvey, Martin

AU - Punitha, P

AU - Jose, Joemon M.

PY - 2010

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AB - In this paper we describe the approaches adopted to generate the runs submitted to ImageCLEFPhoto 2009 with an aim to promote document diversity in the rankings. Four of our runs are text based approaches that employ textual statistics extracted from the captions of images, i.e. MMR [1] as a state of the art method for result diversification, two approaches that combine relevance information and clustering techniques, and an instantiation of Quantum Probability Ranking Principle. The fifth run exploits visual features of the provided images to re-rank the initial results by means of Factor Analysis.

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KW - ImageCLEF

KW - diversity

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DO - 10.1007/978-3-642-15751-6_14

M3 - Conference contribution

SN - 9783642157509

T3 - Lecture Notes in Computer Science

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EP - 141

BT - Multilingual Information Access Evaluation II - Multimedia Experiments

PB - Springer

ER -

Leelanupab T, Zuccon G, Goyal A, Halvey M, Punitha P, Jose JM. University of Glasgow at ImageCLEFPhoto 2009: optimising similarity and diversity in image retrieval. In Multilingual Information Access Evaluation II - Multimedia Experiments: Proceedings of the 10th Workshop of the Cross-Language Evaluation Forum (CLEF 2009). Springer. 2010. p. 133-141. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-642-15751-6_14

University of Glasgow at ImageCLEFPhoto 2009: optimising similarity and diversity in image retrieval

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