This paper presents two metrics for the Nearest Neighbor Classifier that share the property of being adapted, i.e. learned, on a set of data. Both metrics can be used for similari...
The doubling dimension of a metric is the smallest k such that any ball of radius 2r can be covered using 2k balls of raThis concept for abstract metrics has been proposed as a na...
Most research on nearest neighbor algorithms in the literature has been focused on the Euclidean case. In many practical search problems however, the underlying metric is non-Eucl...
Similarity search is widely used in multimedia retrieval systems to find the most similar ones for a given object. Some similarity measures, however, are not metric, leading to e...
Many researchers claim that crosscutting concerns, which emerge in early software development stages, are harmful to software stability. On the other hand, there is a lack of effec...