Library Automation and Digital Archive
LONTAR
Fakultas Ilmu Komputer
Universitas Indonesia

Pencarian Sederhana

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Call Number SEM-357
Collection Type Indeks Artikel prosiding/Sem
Title ALGHORITHM AND PERFORMANCE EVALUATION OF ADAPTIVE MULTIMENSIONAL CLUSTERING TECHNIQUE (308-317)
Author Shinya FUSHIMI*, Masaru KISUREGAWA**, Masaya NAKAYAMA*, Hidehiko TANAKA*, and tohru MOTO-OKA*,;
Publisher Proceedings of acm sigmod 1985 international conference on management of data may 28-31,1985 lamansion hotel austin,texas
Subject
Location
Lokasi : Perpustakaan Fakultas Ilmu Komputer
Nomor Panggil ID Koleksi Status
SEM-357 TERSEDIA
Tidak ada review pada koleksi ini: 48007
This paper proposes the multidimensional clustering technique called GKD-tree method which is fully adaptive to both of tuple and query distributions the method is based on the theoretical analysis of the performance of multidimensional clustering Its algorithm and performance are described it is shown that GKD-tree method can largely reduce the average number of page accesses for several distributions its behavior is analyzed and the modification to the performance GDK-tree method was first developed as the physical database organization of the relational database machine GRACE The implementation issues of GKD-Tree method in the database machine are also discussed.