Výsledky vyhledávání - "Spencer S. Pearson"

Towards a hybrid relational and XML benchmark for loosely-coupled distributed data sources

Autor: Mahesh B Chaudhari, Spencer S. Pearson, Jennifer Ortiz, Suzanne W. Dietrich

Publikováno v: Journal of Systems and Software. 109:78-87

Designed heterogeneous data sources for a hybrid version of the TPC-H enterprise.Developed hybrid LINQ queries over the relational and XML data sources.Evaluated the hybrid benchmark for loosely-coupled distributed data sources.Assessed query perform

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ddbefc00c81865363569f0eb72e309d0
https://doi.org/10.1016/j.jss.2015.07.029

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Autor: Yasin N. Silva, Spencer S. Pearson, Ryan Roberts, Jaime Chon

Publikováno v: Information Systems. 52:149-162

Similarity Joins are extensively used in multiple application domains and are recognized among the most useful data processing and analysis operations. They retrieve all data pairs whose distances are smaller than a predefined threshold e. While seve

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8f849473747db3966044b98e375e2939
https://doi.org/10.1016/j.is.2015.01.008

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Autor: Per-Ake Larson, Spencer S. Pearson, Yasin N. Silva, Mohamed Ali, Walid G. Aref

Publikováno v: The VLDB Journal. 22:395-420

Many application scenarios can significantly benefit from the identification and processing of similarities in the data. Even though some work has been done to extend the semantics of some operators, for example join and selection, to be aware of dat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::67522d1f82ceae8474fd3c906c69dfd4
https://doi.org/10.1007/s00778-012-0296-4

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Exploiting database similarity joins for metric spaces

Autor: Yasin N. Silva, Spencer S. Pearson

Publikováno v: Proceedings of the VLDB Endowment. 5:1922-1925

Similarity Joins are recognized among the most useful data processing and analysis operations and are extensively used in multiple application domains. They retrieve all data pairs whose distances are smaller than a predefined threshold ε. Multiple

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::20787cc5d083a3b014d2dca995d074d0
https://doi.org/10.14778/2367502.2367538

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Index-Based R-S Similarity Joins

Autor: Yasin N. Silva, Spencer S. Pearson

Publikováno v: Similarity Search and Applications ISBN: 9783319119878
SISAP

Similarity Joins are some of the most useful and powerful data processing operations. They retrieve all the pairs of data points between different data sets that are considered similar within a certain threshold. This operation is useful in many situ

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5a3772c9fa42e4e12f3d19f85abe32ff
https://doi.org/10.1007/978-3-319-11988-5_10

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Autor: Jason A. Cheney, Spencer S. Pearson, Yasin N. Silva

Publikováno v: Similarity Search and Applications ISBN: 9783642410611
SISAP

Similarity Joins are recognized among the most useful data processing and analysis operations. They retrieve all data pairs whose distances are smaller than a predefined threshold e. While several standalone implementations have been proposed, very l

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e7c320e18fd71f3a65fd6a009679a9a7
https://doi.org/10.1007/978-3-642-41062-8_27

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