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THE WINDSURF LIBRARY FOR THE EFFICIENT RETRIEVAL OF MULTIMEDIA HIERARCHICAL DATA∗ Ilaria Bartolini, Marco Patella, and Guido Stromei
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Document Date: 2011-05-04 07:22:26


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File Size: 315,37 KB

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City

Minneapolis / Boston / Wavelet / Athens / Vancouver / Reading / Florence / /

Company

Skyline / Database Systems / MySQL / /

Country

Italy / Canada / Greece / /

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Facility

OVERVIEW OF THE WINDSURF LIBRARY The Windsurf library / CUSTOMIZING THE LIBRARY The Windsurf library / Windsurf library / /

IndustryTerm

index-based algorithms / different applications / query processing techniques / query processing algorithm / query processing / non viable solution / similarity search / different algorithms / generic query processing algorithms / extensible software framework / sequential algorithms / image segmentation algorithm / k2 k1 k3 query web site query page / query processing algorithms / transportation problem / above algorithms / pyramid match algorithm / greedy algorithm / out-of-thebox solutions / multimedia applications / ex-novo algorithms / efficient algorithms / /

MarketIndex

SET 100 / /

Organization

idf / US Federal Reserve / /

Person

Marco Patella / Oria / V / Guido Stromei / /

Position

researcher / representative / /

Product

Windsurf / /

ProgrammingLanguage

Java / C++ / /

PublishedMedium

Theoretical Computer Science / Communications of the ACM / /

Technology

ex-novo algorithms / k-NN algorithm / pyramid match algorithm / QP algorithms / image segmentation algorithm / efficient algorithms / relational database / 4 QUERY PROCESSING ALGORITHMS / three index-based algorithms / query processing algorithm / sequential k-NN algorithm / random access / Communication Technology / DBMS / index-based algorithms / generic query processing algorithms / K-means algorithm / alternative query processing algorithms / Java / k-NN-set algorithm / k-NN-imgIdx algorithm / greedy algorithm / RDBMS / Sky-set algorithms / index-based k-NN algorithm / query processing algorithms / different algorithms / then clustered together using a K-means algorithm / /

URL

http /

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