Query and document expansion with medical subject headings terms at medical Imageclef 2008

Authors:
Julien Gobeill;Patrick Ruch;Xin Zhou
Affiliations:
University and Hospitals of Geneva, Service d'Informatique Médicale, Genéve, Switzerland;University and Hospitals of Geneva, Service d'Informatique Médicale, Genéve, Switzerland;University and Hospitals of Geneva, Service d'Informatique Médicale, Genéve, Switzerland
Venue:
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
Year:
2008

Citing 1
Cited 3

Automatic assignment of biomedical categories: toward a generic approach

Bioinformatics

Combining global and local semantic contexts for improving biomedical information retrieval

ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Towards a context sensitive approach to searching information based on domain specific knowledge sources

Web Semantics: Science, Services and Agents on the World Wide Web
Semantic concept-enriched dependence model for medical information retrieval

Journal of Biomedical Informatics

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we report on query and document expansion using Medical Subject Headings (MeSH) terms designed for medical ImageCLEF 2008. In this collection, MeSH terms describing an image could be obtained in two different ways: either being collected with the associated MEDLINE's paper, or being extracted from the associated caption. We compared document expansion using both. From a baseline of 0.136 for Mean Average Precision (MAP), we reached a MAP of respectively 0.176 (+29%) with the first method, and 0.154 (+13%) with the second. In-depth analyses show how both strategies were beneficial, as they covered different aspects of the image. Finally, we combined them in order to produce a significantly better run (0.254 MAP, +86%). Combining the MeSH terms using both methods gives hence a better representation of the images, in order to perform document expansion.