Multimodal-based Diversified Summarization in Social Image Retrieval.

In this paper, we describe our approach and its results for the MediaEval 2015 Retrieving Diverse Social Images task. The main strength of the proposed approach is its exibility that permits to lter out irrelevant images, and to obtain a reliable set of diverse and relevant images. This is done by rst clustering similar images according to their textual descriptions and their visual content, and then extracting images from dierent clusters according to a measure of user’s credibility. Experimental results shown that it is stable and has little uctuation in both single-concept and multi-concept queries.