In this paper we present a clustering and indexing paradigm called Clindex for high-dimensional search spaces. The scheme is designed for approximate similarity searches, where on...
Chen Li, Edward Y. Chang, Hector Garcia-Molina, Gi...
—We consider approaches for similarity search in correlated, high-dimensional data-sets, which are derived within a clustering framework. We note that indexing by “vector appro...
With the proliferation of multimedia data, there is increasing need to support the indexing and searching of high dimensional data. Recently, a vector approximation based techniqu...
Abstract. Nearest neighbor search has a wide variety of applications. Unfortunately, the majority of search methods do not scale well with dimensionality. Recent efforts have been ...
Finding latent patterns in high dimensional data is an important research problem with numerous applications. Existing approaches can be summarized into 3 categories: feature selec...