Revisiting sub-topic retrieval in the ImageCLEF 2009 photo retrieval task

Leelanupab, Teerapong, Zuccon, Guido, & Jose, Joemon M. (2010) Revisiting sub-topic retrieval in the ImageCLEF 2009 photo retrieval task. In ImageCLEF: Experimental evaluation in visual information retrieval [The Information Retrieval Series, Volume 32]. Springer Berlin Heidelberg, pp. 277-294.

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Ranking documents according to the Probability Ranking Principle has been theoretically shown to guarantee optimal retrieval effectiveness in tasks such as ad hoc document retrieval. This ranking strategy assumes independence among document relevance assessments. This assumption, however, often does not hold, for example in the scenarios where redundancy in retrieved documents is of major concern, as it is the case in the sub–topic retrieval task. In this chapter, we propose a new ranking strategy for sub–topic retrieval that builds upon the interdependent document relevance and topic–oriented models. With respect to the topic– oriented model, we investigate both static and dynamic clustering techniques, aiming to group topically similar documents. Evidence from clusters is then combined with information about document dependencies to form a new document ranking. We compare and contrast the proposed method against state–of–the–art approaches, such as Maximal Marginal Relevance, Portfolio Theory for Information Retrieval, and standard cluster–based diversification strategies. The empirical investigation is performed on the ImageCLEF 2009 Photo Retrieval collection, where images are assessed with respect to sub–topics of a more general query topic. The experimental results show that our approaches outperform the state–of–the–art strategies with respect to a number of diversity measures.

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ID Code: 69277
Item Type: Book Chapter
Additional Information: Book Subtitle:
Experimental Evaluation in Visual Information Retrieval
Additional URLs:
DOI: 10.1007/978-3-642-15181-1_15
ISBN: 9783642151804
Divisions: Current > Institutes > Institute for Future Environments
Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2010 Springer
Deposited On: 02 Jun 2014 02:01
Last Modified: 25 Aug 2016 07:30

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