@inproceedings{c1f66157766d489e9436033ca8711b2b,
title = "A novel high-dimensional index method based on the mathematical features",
abstract = "Nowadays the nearest neighbor (NN) search in the high dimensional space can be applied in many fields and it becomes the focus of information science. Usually, R-near neighbor that sets a fixed query range R is used in place of NN search. However, the traditional methods for R-near neighbor can not achieve the satisfactory performance in the high dimensional space due to the curse of dimensionality. Moreover, some methods is based on probabilistic guarantees so it does not provide the 100% accuracy guarantee. To improve the problem, in this paper, we propose a novel idea to build the index structure. This method is based on the mathematical features of the coordinates of the data points. Specifically, we employ the mean value and the standard deviation of the coordinate to index the data point. This method can efficiently solve the R-NN search with the 100% accuracy guarantee in the high dimensional space. Extensive experimental results demonstrate the effectiveness of the proposed methods.",
keywords = "High-dimension, Multimedia, R-near neighbor",
author = "Yu Zhang and Jiayu Li and Ye Yuan",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 2nd International Conference on Big Data Computing and Communications, BigCom 2016 ; Conference date: 29-07-2016 Through 31-07-2016",
year = "2016",
doi = "10.1007/978-3-319-42553-5_22",
language = "English",
isbn = "9783319425528",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "257--271",
editor = "Yu Wang and Ge Yu and Guoren Wang and Yanyong Zhang and Zhu Han",
booktitle = "Big Data Computing and Communications - 2nd International Conference, BigCom 2016, Proceedings",
address = "Germany",
}