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 ...
This paper gives a data structure (UDS) for supporting database retrieval, inference and machine learning that attempts to unify and extend previous work in relational databases, ...
Identification of all objects in a dataset whose similarity is not less than a specified threshold is of major importance for management, search, and analysis of data. Set similari...
A new access method, called M-tree, is proposed to organize and search large data sets from a generic "metric space", i.e. where object proximity is only defined by a di...
We present a shape definition language, called SDC, for retrieving objects based on shapes contained in the histories associated with these objects. It is a small, yet powerful, l...
Rakesh Agrawal, Giuseppe Psaila, Edward L. Wimmers...