M- DATASET LOADING METHOD IN M-TREE USING FASTMAP

摘要

The present invention relates to an M-tree loading method of a dataset using a fast map, which comprises the steps of: mapping a dataset on a metric space to a point on a k-dimensional Euclidean space; aligning the points on the k-dimensional Euclidean space into a one-dimensional sequence; dividing the points of the one-dimensional sequence into contiguous groups; and generating a leaf node for the contiguous group. The dataset is bulk-loaded to the M-tree. Accordingly, a large dataset having the similarity between data objects which is not defined by an Lp distance between two points in the Euclidean space can be efficiently loaded in the M-tree, so that indexing and searching efficiency is more improved than the performance of the existing M-tree.