In visual information retrieval the careful choice of suitable proximity measures is a crucial success factor. The evaluation presented in this paper aims at showing that the dist...
For a collection F of d-variate piecewise linear functions of overall combinatorial complexity n, the lower envelope E(F) of F is the pointwise minimum of these functions. The min...
We consider quantitatively establishing the discriminative power of iris biometric data. It is difficult, however, to establish that any biometric modality is capable of distingui...
Abstract. This paper explores distance measures based on genetic operators for genetic programming using tree structures. The consistency between genetic operators and distance mea...
Many practical applications require that distance measures to be asymmetric and context-sensitive. We introduce Context-sensitive Learnable Asymmetric Dissimilarity (CLAD) measure...
Abstract. We propose a new class of distance measures (metrics) designed for multisets, both of which are a recurrent theme in many data mining applications. One particular instanc...
Abstract. We propose semantic distance measures based on the criterion of approximate discernibility and on evidence combination. In the presence of incomplete knowledge, the dista...
Tree edit distance is one of the most frequently used distance measures for comparing trees. When using the tree edit distance, we need to determine the cost of each operation, bu...
ELKI is a unied software framework, designed as a tool suitable for evaluation of dierent algorithms on high dimensional realvalued feature-vectors. A special case of high dimens...
Elke Achtert, Thomas Bernecker, Hans-Peter Kriegel...
The goal of image categorization is to classify a collection of unlabeled images into a set of predefined classes to support semantic-level image retrieval. The distance measures ...