Abstract: A bulk loading method, for use in a high-dimensional index structure using some parts of dimensions based on an unbalanced binarization scheme, accelerates an index construction and improves a search performance. For the purpose, the bulk loading method calculates a topology of the index by recognizing information for the index to be constructed using a given data set, splits the given data set into sub-sets of data by repeatedly performing an establishment of a split strategy and a binarization based on the calculated topology of the index, if a leaf node is derived from the sub-sets of data divided through a top-down recursive split process, reflects a minimum bounding region of the leaf node on a higher node, and, if a non-leaf node is generated, repeatedly performing the above processes for another sub-set of data to thereby produce a final root node.

Abstract: A bulk loading method, for use in a high-dimensional index structure using some parts of dimensions based on an unbalanced binarization scheme, accelerates an index construction and improves a search performance. For the purpose, the bulk loading method calculates a topology of the index by recognizing information for the index to be constructed using a given data set, splits the given data set into sub-sets of data by repeatedly performing an establishment of a split strategy and a binarization based on the calculated topology of the index, if a leaf node is derived from the sub-sets of data divided through a top-down recursive split process, reflects a minimum bounding region of the leaf node on a higher node, and, if a non-leaf node is generated, repeatedly performing the above processes for another sub-set of data to thereby produce a final root node.