Abstract
In this chapter we explain our participation at ImageCLEF from 2005 to 2009. During these years we have mainly developed systems for the ad hoc and the medical retrieval tasks. Although the different proposed tasks include both visual and textual information, the diverse approaches applied by the participants also include the use of only one type of information. The SINAI group specializes in the management of textual collections. For this reason, our main goal has been to improve the general system by taking advantage of the textual information.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Ah-Pine J, Bressan M, Clinchant S, Csurka G, Hoppenot Y, Renders JM (2009) Crossing textual and visual content in different application scenarios. Multimedia Tools and Applications 42(1):31–56
Aronson AR (2001) Effective mapping of biomedical text to the UMLS metathesaurus: the metamap program. In: Proceedings of the AMIA Symposium, pp 17–21
Chen H, Karger DR (2006) Less is more: probabilistic models for retrieving fewer relevant documents. In: Efthimiadis EN, Dumais ST, Hawking D, Järvelin K (eds) Proceedings of the SIGIR conference, ACM press, pp 429–436
Chevallet JP, Lim JH, Radhouani S (2006) A structured visual learning approach mixed with ontology dimensions for medical queries. In: Accessing Multilingual Information Repositories, Springer, Lecture Notes in Computer Science (LNCS), pp 642–651
Cover T, Thomas J (2006) Elements of information theory. Wiley–Interscience
Díaz-Galiano M, García-Cumbreras M, Martín-Valdivia M, Montejo-Raez A, Ureña López L (2006) SINAI at ImageCLEF 2006. In: Working Notes of CLEF 2006
García-Cumbreras MA, Urena-López LA, Martínez-Santiago F, Perea-Ortega JM (2007) BRUJA System. The University of Jaén at the Spanish task of QA@CLEF 2006. In: Lecture Notes in Computer Science (LNCS), Springer, vol 4730, pp 328–338
Gómez-Soriano JM, Montes-y-Gómez M, Sanchis-Arnal E, Rosso P (2005) A Passage Retrieval System for Multilingual Question Answering. In: 8th International Conference of Text, Speech and Dialogue 2005 (TSD 2005), Springer, Lecture Notes in Artificial Intelligence (LNCS), pp 443–450
Hersh WR, Müller H, Kalpathy-Cramer J (2009) The ImageCLEFmed medical image retrieval task test collection. Journal of Digital Imaging 22(6):648–655
Lana-Serrano S, Villena-Román J, González-Cristóbal J (2008) MIRACLE at ImageCLEFmed 2008: Evaluating Strategies for Automatic Topic Expansion. In: Working Notes of CLEF 2008
Navarro S, Llopis F, Muñoz R (2008) Different Multimodal Approaches using IR–n in ImageCLEFphoto 2008. In: Working Notes of CLEF 2008
Ogilvie P, Callan JP (2001) Experiments using the lemur toolkit. In: Proceedings of TREC
Porter MF (1980) An algorithm for suffix stripping. In: Program 14, pp 130–137
Salton G, Buckley G (1990) Improving retrieval performance by relevance feedback. Journal of American Society for Information Sciences 21:288–297
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Díaz–Galiano, M.C., García–Cumbreras, M.Á., Martín–Valdivia, M.T., Montejo-Ráez, A. (2010). Knowledge Integration using Textual Information for Improving ImageCLEF Collections. In: Müller, H., Clough, P., Deselaers, T., Caputo, B. (eds) ImageCLEF. The Information Retrieval Series, vol 32. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15181-1_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-15181-1_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15180-4
Online ISBN: 978-3-642-15181-1
eBook Packages: Computer ScienceComputer Science (R0)