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

Leelanupab, Teerapong, Zuccon, Guido, Goyal, Anuj, Halvey, Martin, Punitha, P., & Jose, Joemon M. (2010) University of Glasgow at ImageCLEFPhoto 2009 : optimising similarity and diversity in image retrieval. Lecture Notes in Computer Science : Multilingual Information Access Evaluation II. Multimedia Experiments, 6242, pp. 133-141.

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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. The results reveal that our methods based on only text captions consistently improve the performance of the respective baselines, while the approach that combines visual features with textual statistics shows lower levels of improvements.

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ID Code: 72534
Item Type: Journal Article
Refereed: Yes
Additional Information: 10th Workshop of the Cross-Language Evaluation Forum, CLEF 2009, Corfu, Greece, September 30 - October 2, 2009, Revised Selected Papers
Keywords: Interdependent document relevance, Diversity, Novelty
DOI: 10.1007/978-3-642-15751-6_14
ISBN: 978-3-642-15751-6
ISSN: 1611-3349
Divisions: Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2010 Springer-Verlag Berlin Heidelberg
Copyright Statement: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-15751-6_14
Deposited On: 03 Jun 2014 22:39
Last Modified: 23 Jul 2014 22:47

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