This paper introduces a semi-supervised distance metric learning algorithm which uses pair-wise equivalence (similarity and dissimilarity) constraints to improve the original dist...
In applications such as vision and molecular biology, a common problem is to find the similar objects to a given target (according to some distance measure) in a large database. T...
Efficient indexing techniques have been developed for the exact and approximate substructure search in large scale graph databases. Unfortunately, the retrieval problem of structu...
Abstract. In this paper, we present a novel approach to matching cerebral vascular trees obtained from 3D-RA data-sets based on minimization of tree edit distance. Our approach is ...
We introduce a notion, behavioral distance, for evaluating the extent to which processes—potentially running different programs and executing on different platforms—behave si...