Abstract
Although the number of recommending system has increased, many of the existing recommending systems often only offer general-purpose information. In the case of multimedia searches, novelty and unexpectedness are seen as particularly important. In this paper, we propose an image search method with a high degree of unexpectedness by integrating the social tag of Flickr and DBpedia, and using preference data from search logs. We also propose an image search system named Linked Flickr Search, which implemented the proposed method. By evaluation with an unexpectedness index, and by comparing the basic Flickr search functions and flickr wrappr, which is related research, we confirmed that particularly in the initial stages of the search, our proposed system was possible to recommend highly unexpected images.
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Iijima, C., Kimura, M., Yamaguchi, T. (2010). Implementing an Image Search System with Integrating Social Tags and DBpedia. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2010. Lecture Notes in Computer Science(), vol 6278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15393-8_30
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DOI: https://doi.org/10.1007/978-3-642-15393-8_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15392-1
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