An efficient algorithm for approximated self-similarity joins in metric spaces

Sebastián Ferrada, Benjamin Bustos, Nora Reyes

Abstract: Highlights•The proposed algorithm computes a subquadratic number of distances in the worst case.•An average precision of 52% of correct nearest neighbors is reached.•The algorithm offers a viable alternative for k-NN self-similarity joins compared with others.