Using semantic resources in an image retrieval system
Journal Title: Romanian Journal of Human - Computer Interaction - Year 2014, Vol 7, Issue 4
Abstract
In the recent years, with the development of the intelligent devices, users are sharing more and more multimedia data across the Internet using social networks. This is the reason why, web search has also become the main method for people to fulfill their information needs. Nevertheless, searching for diverse data is not that straightforward, since most information retrieval systems base their algorithms on popularity, relevance, rather than dissimilarity. In the CHIST-ERA project MUCKE (Multimedia and User Credibility Knowledge Extraction), we created a multimedia retrieval system that takes into consideration both relevance and diversity. To address the problem of diversification, we explore two approaches: (1) using semantic resources (like YAGO) in the processing of the initial query, and (2) the operations of clustering the results provided by us, based on the images titles or based on their content. In this paper, we present the first approach and we compare the results of our solution with the results provided by the Google search engine.
Authors and Affiliations
Alexandra-Mihaela Siriţeanu, Adrian Iftene
Keywords
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