F
Fausto Rabitti
Researcher at Istituto di Scienza e Tecnologie dell'Informazione
Publications - 90
Citations - 2177
Fausto Rabitti is an academic researcher from Istituto di Scienza e Tecnologie dell'Informazione. The author has contributed to research in topics: Nearest neighbor search & Image retrieval. The author has an hindex of 23, co-authored 90 publications receiving 2112 citations. Previous affiliations of Fausto Rabitti include National Research Council & University of Toronto.
Papers
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Journal ArticleDOI
A model of authorization for next-generation database systems
TL;DR: A fuller model of authorization is presented that fills a few major gaps that the conventional models of authorization cannot fill for next-generation database systems and further formalize the notion of implicit authorization and refine the application of the notionof implicit authorization to object-oriented and semantic modeling concepts.
Posted Content
CoPhIR: a Test Collection for Content-Based Image Retrieval
Paolo Bolettieri,Andrea Esuli,Fabrizio Falchi,Claudio Lucchese,Raffaele Perego,Tommaso Piccioli,Fausto Rabitti +6 more
TL;DR: The experience in building a test collection of 100 million images, with the corresponding descriptive features, to be used in experimenting new scalable techniques for similarity searching, and comparing their results is reported on.
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Approximate similarity retrieval with M-trees
TL;DR: The evidence obtained confirms the hypothesis that a high-quality approximated similarity search can be performed at a much lower cost than that needed to obtain the exact results.
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Building a web-scale image similarity search system
Michal Batko,Fabrizio Falchi,Claudio Lucchese,David Novak,Raffaele Perego,Fausto Rabitti,Jan Sedmidubsky,Pavel Zezula +7 more
TL;DR: The experience in building an experimental similarity search system on a test collection of more than 50 million images and the performance of this technology and its evolvement as the data volume grows by three orders of magnitude is studied.
Journal ArticleDOI
Dynamic partitioning of signature files
TL;DR: Results show that quick filter is economical in space and very convenient for applications dealing with large files of dynamic data, and where user queries result in signatures with high weights, which are particularly interesting for multimedia databases, where integrated access to attributes, text and images must be provided.