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Multimedia, Similarity, and Preferences: Adding Flexibility to Your Information Needs

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A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years

Part of the book series: Studies in Big Data ((SBD,volume 31))

Abstract

Starting from the 90’s, it was easily recognized that commonly adopted search paradigms were not enough to deal with at-the-time emerging novel DB applications, in which the presence of multimedia data and high dimensionality were both key aspects. In this paper we survey the research activity of our group in the last 25 years, therefore going through issues such as indexing, approximate query processing, and support for preference queries, which are now quite well understood. In doing this we also consider the need to provide the users with simple but powerful tools, able to smooth the processes of query creation/customization and of result interpretation. We complete with a look to the novel issues that the “Big Data” era brings to us.

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Notes

  1. 1.

    The (in-)famous “two tigers” example considers a user asking for an image containing two regions each representing a tiger: If a database image contains a single “tiger” region, it is not correct to match both query regions to the single “tiger” region of the database image, since, in this case, information on the number of query regions is lost.

  2. 2.

    Clearly, also SAMs can be used for k-nearest neighbor queries, provided they can index objects’ features.

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Correspondence to Ilaria Bartolini .

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Bartolini, I., Ciaccia, P., Patella, M. (2018). Multimedia, Similarity, and Preferences: Adding Flexibility to Your Information Needs. In: Flesca, S., Greco, S., Masciari, E., Saccà, D. (eds) A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years. Studies in Big Data, vol 31. Springer, Cham. https://doi.org/10.1007/978-3-319-61893-7_8

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  • DOI: https://doi.org/10.1007/978-3-319-61893-7_8

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