Perpustakaan Fakultas Ilmu Komputer

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.