Indexing metric spaces with nested forests

Abstract

Searching for similar objects in a dataset, with respect to a query object and a distance, is a fundamental problem for several applications that use complex data. The main difficulties is to focus the search on as few elements as possible and to further limit the computationally-extensive distance calculations between them. Here, we introduce a forest data structure for indexing and querying such data. The efficiency of our proposal is studied through experiments on real-world datasets and a comparison with previous proposals. © 2012 Springer-Verlag.