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 flexibility that permits to filter out irrelevant images, and to obtain a reliable set of diverse and relevant images. This is done by first clustering similar images according to their textual descriptions and their visual content, and then extracting images from different clusters according to a measure of user’s credibility. Experimental results shown that it is stable and has little fluctuation in both single-concept and multi-concept queries.
Multimodal-based Diversified Summarization in Social Image Retrieval / Dang Nguyen, Duc Tien; Boato, Giulia; De Natale, Francesco; Piras, Luca; Giacinco, Giorgio; Tuveri, Franco; Angioni, Manuela. - 1436:(2015), pp. [1]-[3]. (Intervento presentato al convegno MediaEval 2015 tenutosi a Wurzen nel 14-15, September 2015).
Multimodal-based Diversified Summarization in Social Image Retrieval
Dang Nguyen, Duc Tien;Boato, Giulia;De Natale, Francesco;
2015-01-01
Abstract
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 flexibility that permits to filter out irrelevant images, and to obtain a reliable set of diverse and relevant images. This is done by first clustering similar images according to their textual descriptions and their visual content, and then extracting images from different clusters according to a measure of user’s credibility. Experimental results shown that it is stable and has little fluctuation in both single-concept and multi-concept queries.File | Dimensione | Formato | |
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