%0 Journal Article
%A DUAN Qun1
%A ZHAO A’ni2
%A NIE Wei1
%T High-dimensional data query algorithm based on small-world model
%D 2017
%R 10.3778/j.issn.1002-8331.1603-0001
%J Computer Engineering and Applications
%P 85-89
%V 53
%N 10
%X Based on small-world model, express the high-dimensional feature vector as the network nodes, and then design the high-dimensional index generation algorithm based on K-Means technology and the random approximate neighbor query algorithm. With the appropriate chosen the number of neighbor nodes, the maximum length of query paths and the maximum iterations, the proposed algorithm can meet various query with different precision demands. Experiment demonstrates the algorithm can achieve effective index performance with mass high-dimensional data vectors.
%U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.1603-0001