Ohsu @ MediaEval 2015: Adapting textual techniques to multimedia search

Shiran Dudy, Steven Bedrick

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations


In this paper, we present the motivation, process, results and analysis of results that we have worked on as part of our participation in the 2015 MediaEval Retrieving Diverse Social Images Task. This year, we adapted a recently-published technique for result diversification ("Relational Learning-to-Rank" [13]), borrowed from the world of standard document retrieval. As compared to the original work, our version makes certain changes to the ranking and comparison algorithm, and explores a variety of feature combinations specific to an image retrieval context. The key idea behind our technique was a greedy iterative approach to ranking search results, which attempted to balance relevance with redundancy by comparing candidate results to those already selected by the algorithm. Our approach worked tolerably well on many queries, but there is clearly room for improvement.

Original languageEnglish (US)
JournalCEUR Workshop Proceedings
StatePublished - 2015
EventMultimedia Benchmark Workshop, MediaEval 2015 - Wurzen, Germany
Duration: Sep 14 2015Sep 15 2015

ASJC Scopus subject areas

  • Computer Science(all)


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