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  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.
|Title of host publication||Multilingual Information Access Evaluation II - Multimedia Experiments|
|Subtitle of host publication||Proceedings of the 10th Workshop of the Cross-Language Evaluation Forum (CLEF 2009)|
|Number of pages||9|
|Publication status||Published - 2010|
|Name||Lecture Notes in Computer Science|
|Publisher||Springer Berlin Heidelberg|
- image retrieval