Zobrazeno 1 - 10
of 960
pro vyhledávání: '"Schneider, Michel."'
Publikováno v:
Revista Brasileira de Educação, Vol 16, Iss 48, Pp 793-795 (2011)
Externí odkaz:
https://doaj.org/article/b6b0faa44ad14a1e86b351e405a5a600
Autor:
JULIA, Dominique
Publikováno v:
Histoire de l'education, 1998 Jan 01(77), 78-82.
Externí odkaz:
https://www.jstor.org/stable/41159762
Autor:
Plazas, Julian Eduardo, Bimonte, Sandro, Schneider, Michel, de Vaulx, Christophe, Battistoni, Pietro, Sebillo, Monica, Corrales, Juan Carlos
Publikováno v:
In Data & Knowledge Engineering May 2022 139
Autor:
Kalsi, Pratipal, Hejrati, Nader, Charalampidis, Anastasios, Wu, Pang Hung, Schneider, Michel, Wilson, Jamie RF., Gao, Andrew F., Massicotte, Eric M., Fehlings, Michael G.
Publikováno v:
In Brain and Spine 2022 2
Autor:
Darmont, Jérôme, Schneider, Michel
Publikováno v:
Journal of Database Management, IGI Global, 2000, 11 (3), pp.16-27
We present in this paper a generic object-oriented benchmark (OCB: the Object Clustering Benchmark) that has been designed to evaluate the performances of Object-Oriented Data-bases (OODBs), and more specifically the performances of clustering polici
Externí odkaz:
http://arxiv.org/abs/1611.09172
Autor:
Darmont, Jérôme, Schneider, Michel
Publikováno v:
25th International Conference on Very Large Databases (VLDB 99) (09/1999) 254-265
Performance of object-oriented database systems (OODBs) is still an issue to both designers and users nowadays. The aim of this paper is to propose a generic discrete-event random simulation model, called VOODB, in order to evaluate the performances
Externí odkaz:
http://arxiv.org/abs/0705.0450
Publikováno v:
LNCS, Vol. 1377 (03/1998) 326-340
We present in this paper a generic object-oriented benchmark (the Object Clustering Benchmark) that has been designed to evaluate the performances of clustering policies in object-oriented databases. OCB is generic because its sample database may be
Externí odkaz:
http://arxiv.org/abs/0705.0453
Publikováno v:
LNCS, Vol. 1944 (06/2000) 71-85
We present in this paper three dynamic clustering techniques for Object-Oriented Databases (OODBs). The first two, Dynamic, Statistical & Tunable Clustering (DSTC) and StatClust, exploit both comprehensive usage statistics and the inter-object refere
Externí odkaz:
http://arxiv.org/abs/0705.0281
Akademický článek
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Publikováno v:
Plant Physiology, 2005 May 01. 138(1), 59-66.
Externí odkaz:
https://www.jstor.org/stable/4629803