A k-means-type algorithm is proposed for efficiently clustering data constrained to lie on the surface of a p-dimensional unit sphere, or data that are mean-zero-unit-variance standardized ...

For example, K-means and K-medoids attempt to cluster data by minimizing the distance between a cluster center and each data point.