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A Comprehensive Guide Through the Italian Database Research Over the Last 25 YearsMultimedia, Similarity, and Preferences: Adding Flexibility to Your Information Needs

A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years: Multimedia,... [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.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Comprehensive Guide Through the Italian Database Research Over the Last 25 YearsMultimedia, Similarity, and Preferences: Adding Flexibility to Your Information Needs

Part of the Studies in Big Data Book Series (volume 31)
Editors: Flesca, Sergio; Greco, Sergio; Masciari, Elio; Saccà, Domenico
Bartolini, Ilaria; Ciaccia, Paolo; Patella, Marco
Springer Journals — May 31, 2017
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Publisher
Springer International Publishing
Copyright
© Springer International Publishing AG 2018
ISBN
978-3-319-61892-0
Pages
127 –141
DOI
10.1007/978-3-319-61893-7_8
Publisher site
See Chapter on Publisher Site

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.]

Published: May 31, 2017

Keywords: Range Query; Relevance Feedback; Skyline Query; Query Object; CBIR System

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