Llorente, Ainhoa; Motta, Enrico and Rüger, Stefan
Exploring the semantics behind a collection to improve automated image annotation.
In: 10th Workshop of the Cross-Language Evaluation Forum (CLEF 2009), 30 Sep - 2 Oct 2009, Corfu, Greece, Springer.
Full text available as:
Due to copyright restrictions, this file is not available for public download
The goal of this research is to explore several semantic relatedness measures that help to refine annotations generated by a baseline non-parametric density estimation algorithm. Thus, we analyse the benefits of performing a statistical correlation using the training set or using the World Wide Web versus approaches based on a thesaurus like WordNet or Wikipedia (considered as a hyperlink structure). Experiments are carried out using the dataset provided by the 2009 edition of the ImageCLEF competition, a subset of the MIR-Flickr 25k collection. Best results correspond to approaches based on statistical correlation as they do not depend on a prior disambiguation phase like WordNet and Wikipedia. Further work needs to be done to assess whether proper disambiguation schemas might improve their performance.
Actions (login may be required)