The optimization of similarity queries using metric access methods has been widely discussed in the last decades. Similarity queries consider one object as the query center, and re...
Humberto Luiz Razente, Maria Camila Nardini Barion...
We investigate the problem of approximate similarity (nearest neighbor) search in high-dimensional metric spaces, and describe how the distance distribution of the query object ca...
This paper addresses the efficient processing of similarity queries in metric spaces, where data is horizontally distributed across a P2P network. The proposed approach does not r...
We consider the problem of estimating CPU (distance computations) and I/O costs for processing range and k-nearest neighbors queries over metric spaces. Unlike the specific case ...
Metric access methods (MAMs) serve as a tool for speeding similarity queries. However, all MAMs developed so far are index-based; they need to build an index on a given database. T...