A new method for indexing large amounts of points in high-dimensional space is proposed.The basic principle is as follows:uniformly partition the data space by Lattice vector quantization

store the lattice points by Inverted File

organize the inverted file by Trie tree

and fast access the inverted file by Trie parallel search algorithm.We called this index structure LIFT.Compared with the traditional index methods

the LIFT can build the index structure with low complexity

support very high dimensionality

and take advantage of sparsity of data points in high-dimensional space

etc.The experiments show that for high-dimensional data

the LIFT outperforms the well-known R-tree.