A comparative study of diversity methods for hybrid text and image retrieval approaches

Abstract. This article compares eight different diversity methods: 3 based on visual information, 1 based on date information, 3 adapted to each topic based on location and visual information; finally, for com-pleteness, 1 based on random permutation. To compare the effectiveness of these methods, we apply them on 26 runs obtained with varied meth-ods from different research teams and based on different modalities. We then discuss the results of the more than 200 obtained runs. The results show that query-adapted methods are more efficient than non-adapted method, that visual only runs are more difficult to diversify than text only and text-image runs, and finally that only few methods maximize both the precision and the cluster recall at 20 documents.